Robust genomic predictor of breast and lung cancer metastasis

ABSTRACT

A method of determining the risk of metastasis of breast or lung cancer in a human subject who has or had breast or lung cancer is disclosed herein. The method is based on detecting in a sample from the subject the number of copies per cell of genes and/or genomic regions of a metastatic gene signature set disclosed herein, and determining alternations in the number of copies per cell of the genes and/or genomic regions in the signature set, as compared to the number of copies per cell in non-cancer cells, thereby determining the risk of breast/lung cancer metastasis.

FIELD OF THE DISCLOSURE

This disclosure relates to metastatic gene signatures. More particularly, this disclosure has identified copy number alterations (CNAs) around genes that are over-represented in breast and lung cancer metastases, which serve as the basis for predicting whether a primary tumor will metastasize.

BACKGROUND OF THE DISCLOSURE

Tumor metastasis to distant sites results in 90% of solid tumor cancer deaths (Nguyen, D. X. et al., Nat Rev Genet. 8, 341-52 (2007)). The frequency with which metastasis occurs varies by tumor type and even within a tumor type the time to metastasis can be quite variable from the time at diagnosis to many years in the future. Nonetheless, many of the steps involved in the development of metastasis, invasion beyond the site of origin, escape from apoptosis when detached from the matrix of origin, and colonization of distant sites, are shared across tumor types. These steps are genetically encoded. Metastasis-promoting genes that alter cellular functions in cell lines and in animal models have been identified (Nguyen, D. X. et al., Nat Rev Genet, 8, 341-52 (2007): Vogelstein, B. & Kinzler, K. W., Nat Med. 10, 789-99 (2004); and Hunter, K. W., Br J Cancer, 752-5 (2004)).

Analysis of copy number alterations (CNAs) has proven to be fruitful for identifying recurrent events that are associated with metastasis within specific primary tumor types (Taylor, B. S. et al., Cancer Cell, 18, 11-22 (2010); Pearlman. A. et al., J Probab Stat. 2012, 873570 (2012) and US Patent Publication No. 2014/0221229). CNAs are the genetic changes most commonly observed in human cancers, reflecting the innate chromosomal instability of many tumors (Vogelstein, B. & Kinzler, K. W., Nat Med, 10, 789-99 (2004)). An average one-third of a cancer genome demonstrates CNAs with roughly equal distributions of copy number gains and losses (Beroukhim, R. et al., Nature. 463, 899-905 (2010).). CNAs are accentuated when mutations occur in stability genes that affect the repair of DNA, mitotic recombination or chromosomal segregation (Vogelstein, B. & Kinzler. K. W. Nat Med. 10, 789-99 (2004)). In a previous study, the inventors observed that despite the high frequency of these CNAs throughout the genome, 366 genes within these regions were commonly altered with similar patterns in prostate cancer metastases and primary tumors (Pearlman. A. et al., J Probab Stat, 2012, 873570 (2012)). Sixty-five percent of the genes (241 of 366) were structured on the genome as contiguous gene clumps of two through thirteen genes per clump. The remaining 35% of the genes (125 of 366) were observed as singletons.

Knowledge of these genes and their CNAs could have clinical utility for predicting who might have aggressive disease requiring treatment and whose disease might be indolent. To make such predictions, the inventors developed a metastatic potential score (MPS) that was based on the weighted frequency of specific CNAs overlapping 366 genes observed in prostate cancer metastases (Pearlman, A. et al., J Probab. Stat. 2012, 873570 (2012)). In particular, metastases and metastasis-prone primary tumors all demonstrate enrichment of specific CNAs in one direction. This directionality provided a basis for calculating Z_(genes) scores for the specific genes within the CNAs that included a penalty when the CNA went against the grain of the directionality. The MPS score represented the sum of the Z_(genes) scores, divided by the number of genes being summed. When applied to a small cohort of 60 primary prostate tumors, of which 13 had metastasis outcome, MPS was predictive of the endpoint of metastasis-free survival using a Cox proportional hazards model (Pearlman, A. et al., J Probab Stat. 2012, 873570 (2012)).

In this disclosure, the inventors assessed the prevalence of these CNAs among large numbers of primary prostate cancers, triple negative breast cancers, other breast cancers and lung adenocarcinomas with known outcome. The inventors used a subset of the CNA genes to develop a predictive pan-cancer metastatic potential score (panMPS), because the four cohorts were assayed on different array platforms that represented different CNA genes. The panMPS was derived by using 295 of the 366 CNA genes that overlapped across all array platforms. Although 71 CNA genes were not represented in the panMPS, most of these were located in multi-gene clumps, thereby capturing the content of 67 of the 69 clumps, with no loss in the predictive accuracy for the panMPS relative to the MPS using 366 genes (Table 13, except the two pseudogenes (C8orf16 and ERW)). The inventors also observed high frequencies of these alterations in metastatic cell lines for tumors of eight different origins.

BRIEF DESCRIPTION OF THE DRAWINGS

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FIGS. 1A-1D. Receiver operating characteristic curves estimate the accuracy of the panMPS for predicting metastatic outcome for prostate cancer (A. MSK cohort, B. Duke cohort), triple negative breast cancer (C. Montefiore cohort) and lung adenocarcinoma (D. MSKCC cohort). For prostate cancer, panMPS was predictive of mPT and iPT status in both the MSK and Duke cohorts. In addition, preoperative PSA, biopsy Gleason score, and percent genomic instability were predictive of mPT and iPT status in the MSK cohort, only. The AUC is indicated for each curve.

FIGS. 2A-2D. Kaplan Meier analysis shows that MPS is associated with overall survival. A. Metabric breast cancer (N=1980); B. TCGA breast cancer (N=1054); C. TCGA prostate cancer (N=482): D. TCGA lung adenocarcinoma (N=483). Y-axis indicates overall survival probability and X axis indicates survival time. p-value calculated by log-rank test.

FIG. 3. MPS genes show higher functional and biomarker annotations than 100 random sets of 366 genes. Number of genes found to have Pubmed citations for metastasis functions for random sets of genes (grey) and MPS genes (black). There were 2 outliers the exceeded the upper fence, the MPS genes (N=60) and one random set (N=69).

FIG. 4A-4C. Chromosome 8p exhibiting 70 genes predictive of metastatic potential, including genes that occur in clumps (A). Each bar represents a gene as it is located on the chromosome (X-axis) whereas the height of the bar denotes a Zgenes score (Y-axis) that measures the gene CNA profile's ability to predict the metastatic potential of a primary prostate cancer. Arrows on top of some of the bars indicate that the gene has been validated in prior metastasis studies as a biomarker or to have metastatic function. Clump region #26 (nine gene segment) and clump region #30 (seven gene segment) are highlighted in the top panel and zoomed in (B) (Clump region #26) and (C) (Clump region #30).

FIG. 5A-5B. Small sets of high Zgenes score genes predict metastatic outcome and panMPS almost as well as all MPS genes for all four cohorts. ROC-AUCs estimating metastatic outcome and linear regression (r²) estimating panMPS for all four cohorts demonstrate reduction of complexity for high Z_(genes) score genes. AUC (A) and r² (B) estimating metastatic outcome and panMPS, respectively, for simplified versions of MPS, including those with high Z_(genes) scores. Numbers of genes and clumps are indicated for different Z_(genes) scores. * one gene per clump.

FIG. 6A-6C. Chromosome 8q exhibiting 75 genes predictive of metastatic potential, including genes that occur in clumps (A). Each bar represents a gene as it is located on the chromosome (X-axis) whereas the height of the bar denotes a Z_(gene) score (Y-axis) that measures the gene CNA profile's ability to predict the metastatic potential of a primary prostate cancer. Arrows on top of some of the bars indicate that the gene has been validated in prior metastasis studies as a biomarker or to have metastatic function. Red colored bars/arrows indicate a singleton gene or one member clump. Clump region #33 (six-gene segment) and clump region #40 (four-gene segment) are highlighted in (A) and zoomed in (B) (Clump region #33) and (C) (Clump region #40).

FIG. 7A-7C. Chromosome 16q exhibiting 74 genes predictive of metastatic potential, including genes that occur in clumps (A). Each bar represents a gene as it is located on the chromosome (X-axis) while the height of the bar denotes a Z_(genes) score (Y-axis) that measures the gene CNA's ability to predict the metastatic potential of a primary prostate cancer tumor. Arrows on top of some of the bars indicate that the gene has been validated in prior metastasis studies as a biomarker or to have metastatic function. Red colored bars/arrows indicate a singleton gene or one member clump. Clump region #57 (8-gene segment) and clump region #58 (13-gene segment) are highlighted in (A) and zoomed in (B) (Clump region #57) and (C) (Clump region #58).

DETAILED DESCRIPTION

This disclosure provides a risk model that reliably predicts those tumors that are likely to metastasize, while minimizing the false positive rate and increasing the specificity of treatment decisions.

The risk model has been developed through the identification of copy number alterations (CNAs) around genes that were over-represented in metastases and primary tumors that later progressed to metastases. These CNAs are predictive of whether a primary tumor will metastasize. Cross-validation analysis has revealed a predictive accuracy of 80.5% and log rank analysis of the metastatic potential score has been shown to be significantly related to the endpoint of metastasis-free survival (p=0.014). In contrast to other reported risk models, the risk model disclosed herein based on the study of CNAs predicts distant metastasis progression as the clinical endpoint without the use of intermediate endpoints (such as biochemical markers of progression). The hierarchy of the genes and genomic regions that contribute to the prediction of metastatic potential has also been determined.

Accordingly, disclosed herein is a method for determining the risk of metastasis of breast or lung cancer in a human subject who has or had breast or lung cancer. This method is based on determining in a breast or lung sample from the subject, copy number alterations (CNAs) of genes and genomic regions of a metastatic gene signature set, and correlating the CNAs with a risk of breast or lung cancer metastasis.

The present method is useful for diagnosing breast and lung cancer in fluid aspirates or lavage or cell-free DNA in serum, monitoring therapeutic response in tissue, fluid or blood samples, and monitoring disease recurrence or progression in tissue, fluid or blood samples.

Metastatic Gene Signature

Metastatic gene signatures have been developed by the present inventors as described in detail in U.S. patent application Ser. No. 14/114,057 and hereinbelow. Accordingly, in one embodiment, this disclosure provides a metastatic gene signature set which includes the 366 genes identified herein, set forth in Table 13 (Table 13 has 368 genes, but the two pseudogenes C8orf16 and ERW are excluded from the gene signature set).

As displayed in Table 3, the 366 genes include a number of “clumps”, each clump identified by a “Clump Index Number”. A “clump”, as used herein, refers to a group of genes that are adjacent to one another on the chromosome, and copy number alterations are detected for the genomic region which includes this group of genes in connection with prostate cancer metastasis. A multi-member clump may include both drivers (genes that cause or more directly associate with metastasis) and passengers (genes that indirectly associate with metastasis because of its close proximity of a metastasis driver gene).

The term “genomic region” is used herein interchangeably with the term “clump”, and is typically used herein in conjunction with the name of a member gene within the genomic region or clump. For example, the PPP3CC gene listed in the first row of Table 14 belongs to Clump Index 26, which also includes the genes KIAA1967, BIN3, SORBS3, PDLIM2, RHOBTB2, SLC39A14, EGR3, and C8orf58. Therefore, Clump Index 26 is also referred to herein as “the PPP3CC genomic region”.

While many of the 366 genes belong to clumps, some of the genes do not belong to any clump and copy number alterations have been identified specifically around each of these genes in connection with metastasis of prostate cancer. For example, as shown in Table 14 (with “NA” in the Clump Index column), CDH13, CDH8, CDH2 CTD8, COL19A1, YWHAG, and ENOX1, among many others, are genes which do not belong to any clump.

In other embodiments, this disclosure provides smaller metastatic gene signature sets which include at least 80, at least 40, at least 20, or at least 12, non-overlapping genes and/or genomic regions listed in Table 14.

By “non-overlapping” it is meant that the genes selected to constitute a smaller signature set do not belong to the same genomic region or clump.

Accordingly, in one embodiment, a metastatic gene signature set includes at least the top 80 genes and genomic regions shown in Table 14.

In another embodiment, a metastatic gene signature set includes at least the top 40 genes and genomic regions shown in Table 14.

In still another embodiment, a metastatic gene signature set includes at least the top 20 genes and genomic regions shown in Table 14.

In yet another embodiment, a metastatic gene signature set includes at least the top 12 genes and genomic regions shown in Table 14.

Determination of Copy Number Alterations (CNAs)

A copy number alteration is a variation in the number of copies of a gene or genomic region present in the genome of a cell. A normal diploid cell typically has two copies of each chromosome and the genes contained therein. Copy number alterations may increase the number of copies, or decrease the number of copies.

To determine whether there is any copy number alteration for a given gene or genomic region, a sample is obtained from a subject of interest, wherein the sample can be from lung or breast tissue. A breast sample refers to a cell or tissue sample taken from the breast of a subject of interest which sample contains genomic DNA to be analyzed for CNAs. A lung sample refers to a cell or tissue sample taken from the lung of a subject of interest which sample contains genomic DNA to be analyzed for CNAs. Methods of procuring cell and tissue samples are well known to those skilled in the art, including, for example, tissue sections, needle biopsy, surgical biopsy, and the like. For a cancer patient, cells and tissue can be obtained from a tumor. A cell or tissue sample can be processed to extract, purify or partially purify, or enrich or amplify the nucleic acids in the sample for further analysis.

Nucleic acid probes are designed based on the genes and genomic regions of a metastatic signature gene set which permit detection and quantification of CNAs in the genes and genomic regions.

In one embodiment, the probes are composed of a collection of nucleic acids that specifically hybridize to the full set of 366 genes of the metastatic signature gene set.

In another embodiment, the probes are composed of a collection of nucleic acids that specifically hybridize to the top 80 genes and genomic regions shown in Table 14.

In still another embodiment, the probes are composed of a collection of nucleic acids that specifically hybridize to the top 40 genes and genomic regions shown in Table 14.

In yet another embodiment, the probes are composed of a collection of nucleic acids that specifically hybridize to the top 20 genes and genomic regions shown in Table 14.

In a further embodiment, the probes are composed of a collection of nucleic acids that specifically hybridize to the top 12 genes and genomic regions shown in Table 14.

By “specifically hybridize” it is meant that a nucleic acid probe binds preferentially to a target gene or genomic region under stringent conditions, and to a lesser extent or not at all to other genes or genomic regions.

“Stringent conditions” in the context of nucleic acid hybridization are known in the art, e.g., as described in Sambrook, Molecular Cloning: A Laboratory Manual (2^(nd) ed.) vol. 1-3, Cold Spring Harbor Laboratory, Cold Spring Harbor Press, New York (1989). Generally, highly stringent hybridization and wash conditions are selected to be about 5° C. lower than the thermal melting point for a specific sequence at a defined ionic strength and pH. An example of highly stringent hybridization conditions is 42° C. in standard hybridization solutions. An example of highly stringent wash conditions include 0.2×SSC at 65° C. for 15 minutes. An example of medium stringent wash conditions is 1×SSC at 45° C. for 15 minutes. An example of a low stringency wash is 4×-6×SSC at room temperature to 40° C. for 15 minutes.

Nucleic acid probes for purposes of this invention should be at least 15 nucleotides in length to permit specific hybridization to a target gene or genomic region, and can be 50, 100, 200, 400, 600, 800, 1000, or more nucleotides in length, or of a length ranging between any of the two above-listed values. A nucleic acid probe designed to specifically hybridize to a target gene can include the full length sequence or a fragment of the gene. A nucleic acid probe designed to specifically hybridize to a specific target genomic region can include at least a fragment of the genomic region, e.g., at least the full length sequence or a fragment of a gene (any gene) within the genomic region. Alternatively, a nucleic acid probe shares at least 801%, 85%, 90%, 95%, 98%, 99% or greater sequence identity with the target gene to permit specific hybridization.

The hybridized nucleic acids can be detected by detecting one or more labels attached to the sample or probe nucleic acids. The labels can be incorporated by a variety of methods known in the art, and include detectable labels such as magnetic beads, a fluorescent compound (e.g., Texas red, rhodamine, green fluorescent protein and the like), radio isotope, enzymes, colorimetric labels (e.g., colloidal gold particles). In other embodiments, the sample or probe nucleic acids can be conjugated with one member of a binding pair, and the other member of the binding pair is conjugated with a detectable label. Binding pairs suitable for use herein include biotin and avidin, and hapten and a hapten-specific antibody.

A number of techniques for analyzing chromosomal alterations are well known in the art. For example, fluorescence in-situ hybridization (FISH) can be used to study copy numbers of individual genetic loci or regions on a chromosome. See, e.g., Pinkel et al., Proc. Natl. Acad. Sci. USA 85: 9138-9142 (1988). Comparative genomic hybridization (CGH) can also be used to detect copy number alterations of chromosomal regions. See. e.g., U.S. Pat. No. 7,638,278.

In some embodiments, hybridization is performed on a solid support. For example, probes that specifically hybridize to signature genes and genomic regions can be spotted or immobilized on a surface, e.g., in an array format, and subsequently samples containing genomic DNA are added to the array to permit specific hybridization.

Immobilization of nucleic acid probes on various solid surfaces and at desired densities (e.g., high densities with each probe concentrated in a small area) can be achieved by using methods and techniques known in the art. See, e.g., U.S. Pat. No. 7,482,123 B2. Examples of solid surfaces include nitrocellulose, nylon, glass, quartz, silicones, polyformaldehyde, cellulose, cellulose acetate; and plastics such as polyethylene, polypropylene, polystyrene, and the like; gelatins, agarose and silicates, among others. High density immobilization of nucleic acid probes are used for high complexity comparative hybridizations which will reduce the total amount of sample nucleic acids required for binding to each immobilized probe.

In some embodiments, the arrays of nucleic acid probes can be hybridized with one population of samples, or can be used with two populations of samples (one test sample and one reference sample). For example, in a comparative genomic hybridization assay, a first collection of nucleic acids (e.g., sample from a possible tumor) is labeled with a first label, while a second collection of nucleic acids (e.g., control from a healthy cell or tissue) is labeled with a second label. The ratio of hybridization of the nucleic acids is determined by the ratio of the two labels binding to each member in the array. Where there are genomic deletions or amplifications, differences in the ratio of the signals from the two labels will be detected and provide a measure of the copy number.

The calculated metastatic potential score is compared to a reference distribution of samples (the metastatic potential score determined from a population of men with prostate cancer with metastasis-free survival clinical outcome information). Such reference distributions can be predetermined or calculated side-by-side in the same experiment as the sample being investigated. Therefore, an increase in the metastatic potential score as compared to the reference distributions is correlated with an increased risk of metastasis of prostate cancer. According to this disclosure, a one-point increase in the metastatic potential score corresponds to an odds ratio of 6.3 for progression to metastasis (p=0.01).

Determination of Risk

Once copy number alterations for each of a metastatic signature gene set have been determined, the risk for metastasis can be correlated with the copy number alterations detected. An increase in the copy number per cell of the sample for one or more of the genes or genomic regions of a metastatic signature gene set disclosed herein, whose amplifications have been associated with metastatic prostate cancer, will indicate a higher risk of metastasis as compared to a control (e.g., a sample obtained from a healthy individual) in which no increase in the copy number occurs. On the other hand, a decrease in the sample in the copy number for one or more of the genes or genomic regions of a metastatic signature gene set disclosed herein, whose deletions have been associated with metastatic prostate cancer, will indicate a higher risk of metastasis as compared to a control in which no decrease in the copy number is observed.

For example, for a metastatic signature gene set composed of the top 20 genes and genomic regions listed in Table 6, an increase in the copy number per cell of the sample for all of the SLCO5A1 genomic region, the KCNB2 genomic region, the KCNH4 genomic region, the JPH1 genomic region, the NCALD genomic region, and the YWHAG gene, and a decrease in the sample in the copy number per cell of the sample for all of the PPP3CC genomic region, the SLC7A5 genomic region, the SLC7A2 genomic region, the CRISPLD2 genomic region, the CDH13 gene, the CDH8 gene, the CDH2 gene, the ASAH1 genomic region, the CTD8 gene, the MEST genomic region, the COL19A1 gene, the MAP3K7 genomic region, the NOL4 genomic region, and the ENOX1 gene, correlate with an increased risk of breast cancer or lung cancer metastasis. However, it is not necessary for all the genes and genomic regions within a signature set to change in the same direction as set forth in Table 6 in order to have a reasonably reliable prediction of the risk. That is, an increased risk can be predicted based on an increase in the copy number per cell of the sample for one or more, preferably a plurality of, the SLCO5A1 genomic region, the KCNB2 genomic region, the KCNH4 genomic region, the JPH1 genomic region, the NCALD genomic region, and the YWHAG gene, and/or a decrease in the sample in the copy number per cell of the sample for one or more, preferably a plurality of, the PPP3CC genomic region, the SLC7A5 genomic region, the SLC7A2 genomic region, the CRISPLD2 genomic region, the CDH13 gene, the CDH8 gene, the CDH2 gene, the ASAH1 genomic region, the CTD8 gene, the MEST genomic region, the COL19A1 gene, the MAP3K7 genomic region, the NOL4 genomic region, or the ENOX1 gene. By “plurality” it is meant at least 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 of the top 20 genes and gene regions listed in Table 14.

This disclosure also provides a quantitative measure of the risk based on the copy number alterations of a signature gene set disclosed herein. More specifically, the risk of metastasis has been found to correlate with a metastatic potential score calculated based on the formula:

${M({SM})} = {\sum\limits_{i}^{n}{{Zadjust}_{i}*{{Dir}_{sig}(i)}*{{Dir}_{samp}(i)}}}$

That is, for a particular gene or genomic region, if the CNA of the signature and the sample are in the same direction (amplified or deleted), the coefficient (coefficient is shown as Dir, wherein Dir (i)=Dir_(sig)(i)*Dir_(samp)(i) in the formula above) will be 1, the logistic adjusted Z-score (Zadjust) for this gene or genomic region will be added: if in opposing directions, the coefficient will be −1, the logistic adjusted Z-score (Zadjust) for the gene or genomic region will be subtracted; and if Dir_(samp)(i)=0, then the entire term will not count towards the score. Thus, essentially, the logistic adjusted Z-scores from genes (i . . . n) that match the metastasis signature are added, whereas from genes that mismatch the signature are subtracted. The logistic adjusted Z-scores (Zadjust) for each of the 366 genes of the full metastatic signature set are found in Table 14.

The calculated metastatic potential score is compared to a reference distribution of samples (the metastatic potential score determined from a population of patients with breast or lung cancer with metastasis-free survival clinical outcome information, also called herein “the reference metastatic potential score”). Such reference distributions can be predetermined or calculated side-by-side in the same experiment as the sample being investigated. In many of the embodiments, the reference metastatic potential score equals to or is approximately 1.0. Therefore, an increase in the metastatic potential score of a test subject as compared to the control score from the reference distributions is correlated with an increased risk of metastasis of breast or lung cancer. According to this disclosure, a one-point increase in the metastatic potential score corresponds to an odds ratio of 6.3 for progression to metastasis (p=0.01). In some embodiments, an increase in the metastatic potential score as compared to a reference score by at least about 0.5, 0.53, 0.56, 0.58, 0.6, 0.65, 0.7 or greater, is considered to represent a significantly high risk of metastasis.

The disclosed method for predicting the likelihood of distant metastases represents a significant advancement in the diagnosis and treatment of breast and lung cancer. This predictor may be important for correctly categorizing patients at the time of diagnosis and can lead to a choice of therapy that would maximize their chances of survival and minimize adverse side effects if aggressive treatment can be avoided. Thus, both treatment outcomes and quality of life could be improved. In addition, because the proposed tool, tumor genomic analysis, is comprehensive for identifying the genetic changes that are associated with pathogenesis and metastases, there is a greater likelihood of selecting a sufficient number of markers that are both sensitive and specific predictors. Furthermore, because these genomic alterations are themselves susceptible to manipulation with drugs, radiation or other therapies, they could provide a basis for assessing intermediate endpoints, such as androgen sensitivity and response to radiation. Ultimately, copy number alterations could guide the development of individually tailored therapies, including for cancers other than prostate, breast or lung.

Methods for detecting Copy Number Alterations (CNAs)

The following methods can be utilized in detection of copy number alterations.

Muliplex Ligation-Dependent Probe Amplification (MLPA)

Multiplex Ligation-dependent Probe Amplification (MLPA®) is a high-throughput method developed to determine the copy number of up to 50 genomic DNA sequences in a single multiplex PCR-based reaction. MLPA is easy to perform, requires only 20 ng of sample DNA and can distinguish sequences differing in only a single nucleotide. The MLPA reaction results in a mixture of amplification fragments ranging between 100 and 500 nt in length which can be separated and quantified by capillary electrophoresis. The equipment necessary for MLPA is identical to that for performing standard sequencing reactions: a thermocycler and a fluorescent capillary electrophoresis system. Comparison of the peak pattern obtained on a DNA sample to that of a reference sample indicates which sequences show aberrant copy numbers.

Fundamental for the MLPA technique is that it is not the sample DNA that is amplified during the PCR reaction, but MLPA probes that hybridise to the sample DNA. Each MLPA probe consists of two probe oligonucleotides, which should hybridise adjacent to the target DNA for a successful ligation. Only ligated probes can be exponentially amplified by PCR. In contrast to standard multiplex PCR, only one pair of PCR primers is used for the MLPA PCR reaction, resulting in a more robust system. This way, the relative number of fragments present after the PCR reaction depends on the relative amount of the target sequence present in a DNA sample. MLPA protocol is described in detail in Eijk-Van Os P G. et al. (Methods Mol Biol. 2011; 688:97-126).

Quantitative Polymerase Chain Reaction (qPCR)

Quantitative real-time PCR (qPCR) is PCR visualized in real time by the use of fluorescent or intercalating dyes used to measure gene expression or gene quantification including including contiguous gene deletions or duplications. A simple method is described to quantify DNA copy number from human samples in Lijiang et al. (Curr Protoc Hum Genet. 2014 Jan. 21; 80: 7.21.1-7.21.8).

PCR-Based Detection of DNA Copy Number Variation (dPCR)

A method for PCR-based detection of copy number of target genes in human genome using TaqMan copy number assay is described in MehrotraM. (Methods Mol Biol. 2016; 1392:27-32. doi: 10.1007/978-1-4939-3360-0_3).

Genomic Sequencing

Whole genome copy number alteration analyses and the computational approaches that can be utilized are discussed in Pirooznia et al. (Front Genet., 2015; 6: 138). In some embodiments, the whole genome analysis is a Next Generation (NextGen) sequencing based assay. Next-generation sequencing refers to non-Sanger-based high-throughput DNA sequencing technologies. Millions or billions of DNA strands can be sequenced in parallel, yielding substantially more throughput and minimizing the need for the fragment-cloning methods that are often used in Sanger sequencing of genomes. Next Generation Sequencing is described in Behjati et al. (Arch Dis Child Educ Pract Ed. 2013 December; 98(6): 236-238.).

The present description is further illustrated by the following examples, which should not be construed as limiting in any way. The contents of all cited references (including literature references, issued patents, and published patent applications as cited throughout this application) are hereby expressly incorporated by reference.

EXAMPLES Example 1: Materials and Methods

Predictive CNAs, MPS and panMPS.

This disclosure provides an in-depth comparison of a set of 366 genes whose CNAs are predictive of breast or lung cancer metastasis. The contributions of these genes to MPS as Z_(genes) scores were reported previously (Pearlman, A. et al., J Probab Stat. 2012, 873570 (2012) and US Patent Publication No. 2014/0221229). These are calculated by assigning each probe on the array to a gene, provided it falls within 10,000 bp upstream or downstream of the transcription start or stop site. z=(X−μ)/σ as described previously (4). The score for a gene, X, is subtracted by the mean, p, of the background distribution of selection model scores and divided by the standard deviation, a, of the background distribution of selection model scores. A conservative background distribution of selection model scores was calculated by sampling the top 5th percentile of amplified or deleted probes from all genes on the array with the same number of probes as the gene in question. The result is a Z_(genes) score for each gene in the genome that is represented on the array. Alternatively, the complete set of genomic CNAs was used to calculate percent genomic instability. The CNA methodology is assay platform-independent, but requires that genomic DNA signal intensities are measured within the regions of the metastasis signature. In this study, the analysis was conducted on primary data sets reported here utilizing the Affymetrix Oncoscan FFPE V3 array (Foster, J. M. et al., BMC Med Genomics 8, 5 406 (2015)), and on previously generated data sets assayed on Agilent 240K and other arrays (Hieronymus, H. et al., Proc Nal Acad Sci USA 111, 11139-44 (2014)). For comparison of cohorts from different platforms, the corresponding numbers of the MPS genes were reduced to include only those that overlapped (366 to 295 genes), representing the panMPS.

Cohorts, Tissue and Sample Processing

A prostate cancer radical prostatectomy cohort of 37 men that progressed to metastasis (mPTs) and 24 men that were free from biochemical recurrence and metastases (iPTs) after at least five years of follow up was collected at Duke University (Duke cohort—Table 10A). The Duke cohort had a case-control design that matched mPTs and iPTs for age, race, pathological stage, margin status, Gleason score, and surgery year. Tumor regions were microdissected, extracted for DNA, and assayed on the Oncoscan FFPE V3 array (Affymetrix Oncoscan Service, Santa Clara, Calif.).

A second prostate cancer cohort, comprised of 25 mPTs along with 157 iPTs was collected at Memorial Sloan-Kettering Cancer Center (MSK cohort—Table 10A). The collection, extraction and data generation for the second cohort has been described previously (Hieronymus, H. et al., Proc Natl Acad Sci USA 111, 11139-44 (2014)). The MSK cohort represented a consecutive case-cohort design with non-recurrent, non-metastatic outcome samples making up a disproportionate number. Unlike the Duke samples, these samples were not matched on any criteria. The MSK cohort was comprised of fresh frozen radical prostatectomies. The Duke and MSK cohorts differed in their length of follow-up, clinical and pathologic attributes and biochemical recurrence and metastasis outcomes (Table 10A). The Duke cohort was collected for individuals with greater than five years follow-up since the majority of prostate cancers recur or metastasize within this timeframe. To achieve parity for prediction modeling and maximizing the metastasis informativeness of each patient, the MSK cohort was filtered for subjects that had at least five years of follow-up. Also, for both cohorts, metastasis negative subjects treated with radical prostatectomy and adjuvant radiation and/or hormonal therapy were excluded from analysis to provide a more homogeneous iPT group.

A triple negative breast cancer radical surgical cohort of 28 women that progressed to metastasis (mBCs) and 13 women that were free from local recurrence and metastasis (iBCs) after at least five years of follow up was collected at Montefiore Medical Center (Montefiore cohort—Table 10B). The Montefiore cohort had a case-control design that matched mBCs and iBCs for age, race, pathological stage, margin status, and surgery year. The breast cancer tumor blocks from each patient were handled in a fashion similar to the prostate cancer tumor blocks and reviewed by a single pathologist and shown to be negative for expression of the estrogen receptor, progresterone receptor and HER2/NEU protein, as judged by immunohistochemistry. Tumor regions were microdissected, extracted for DNA, and assayed on the Oncoscan FFPE V2 array (Affymetrix Oncoscan Service, Santa Clara, Calif.).

Tumor tissue from 199 primary lung adenocarcinomas was collected at the time of resection between 1996 and 2006 at MSKCC and analyzed for CNAs on Agilent 44K CGH arrays, as described previously (Chitale, D. et al., Oncogene 28, 2773-83 (2009)). From this cohort, all available early stage (1A, B and 2A,B) samples that progressed to mortality (mLA, n=23) and late stage (3B and 4) samples that remained alive for greater than one year of follow up (iLA, n=10) (Table 10C) were selected.

This study was reviewed and approved by the Institutional Review Boards at Albert Einstein College of Medicine, New York University School of Medicine, and Duke University.

The copy number alterations (CNAs) level 3 data from cBioPortal for cancer genomics for 3998 patients with three tumor types (Gao J. et al., Sci Signal 6:p11, 2013, Cerami E. et al., Cancer Discov, 2:401-4, 2012) were downloaded. Metabric and TCGA provisional study were selected for breast invasive carcinoma, TCGA provisional study was selected for Lung adenocarcinoma and TCGA provisional study was selected for prostate adenocarcinoma (Milioli H H. Et al., PLoS One, 10:e0129711, 2015, Pereira B. et al., Nat Commun, 7:11479, 2016). panMPS score was calculated based on CNAs for these studies. Univariate Cox proportional hazards model was used to examine the association between MPS and survival. Overall survival was used as the endpoint.

Cell Lines.

CNA data from 183 human cell lines of metastatic origin were available from the Cancer Cell Line Encyclopedia (CCLE). These cell lines included breast, lung adeno, pancreas, large intestine, lymphoid, melanoma, lung small cell and stomach cancers. The data were generated using the Affymetrix SNP 6.0 arrays, as described previously (Beroukhim R. et al., Nature. 463:899-905, 2010).

MPS and panMPS

MPS was calculated based on genomic CNAs overlapping 366 genes with a higher score indicating a greater likelihood of metastasis, as described previously (Pearlman, A. et al., J Probab Stat. 2012, 873570 (2012)). The pan cancer MPS or panMPS was derived from the MPS by using a subset of 295 genes from the MPS. Univariate and multivariate logistic regression and Cox proportional hazards survival models for prostate cancer were evaluated for panMPS, pre-surgery predictors (PSA, clinical stage, biopsy Gleason), demographic variables (age at diagnosis and race), and percent genomic instability, as described previously (Hieronymus, H. et al., Proc Natl Acad Sci USA 111, 1113944 (2014)). The logistic regression and Cox models were also tested for triple negative breast cancer and lung adenocarcinoma. AUC and concordance index were calculated for the logistic and Cox models, respectively.

Functions of MPS Genes in Driving Metastases

To gauge whether the MPS genes played a role in metastasis, we performed in-silico analysis by running three comprehensive queries with the RISmed package from R. First we performed a general Pubmed citation query by searching for the 366 gene IDs and the terms “metastasis”, “metastases” or “metastatic” in the title or abstract of the publication (“metastasis IDs”). Next, we appended this query to capture metastasis functions by adding search terms, “apoptosis assay”, “TUNEL”, “Matrigel”, “invasion assay”, “wound healing assay”, “migration assay”, “MTT”, “BrDU”, “proliferation assay”, “SiRNA” and “xenograft” (“metastasis functions”). Then, the title query was appended to capture predictive biomarkers of metastasis by adding search terms, “Cox”, “Kaplan-Meier” and “hazard ratio” (“metastasis biomarkers”). The MPS gene queries were manually curated and confirmed for accuracy by two reviewers. The annotation frequency was computed for each query type. To assess the significance of these annotations for the MPS genes compared to the remaining, non-overlapping 18,638 protein coding genes an enrichment analysis based on the hypergeometric distribution was performed for the MPS genes versus all 19,004 protein coding genes annotated using the same query search terms to create expanded gene sets for metastasis ID, metastasis functions, metastasis biomarkers and chemokine ID.

Reduction of Complexity

To determine whether the genes with the highest Z_(genes) score among the clumps could predict outcomes as well as the full set of panMPS genes, we calculated AUC and r² for simplified MPS versions by using genes with Z_(genes) score ≥3, Z_(genes) score ≥4, or highest Z_(genes) score within a clump.

Example 2. panMPS Predicts Risk of Metastasis Outcome for Prostate and Triple Negative Breast Cancers and Lung Adenocarcinomas

The clinical validity of panMPS as a predictor of metastasis outcome was tested in studies of prostate and triple negative breast cancers and lung adenocarcinomas. For the outcome of prostate cancer metastasis, univariate logistic regression of panMPS resulted in significant odds ratios and areas under receiver-operator curves (AUCs) for the MSK (OR 6.01, AUC 0.71, p=0.001) and the Duke cohorts (OR 11.39, AUC 0.72, p=0.004) (Table 1A and FIG. 1). Pre-operative PSA and pathology stage improved the AUC in logistic regression analysis of the MSK cohort, but, because of matching between mPTs and iPTs, did not lead to improvement in the Duke cohort (Table 5). In univariate logistic regression analysis of the MSK cohort, percent genomic instability as a predictor had an OR 1.17, AUC=0.74, p=1.4×10⁵; however, this predictor did not reach statistical significance in the Duke cohort (OR 1.04, AUC=0.80, p=0.12) (Table 5). This indicates that percent genomic instability, while useful in the MSK cohort, was not an independent and robust predictor of metastasis. Thus, the subset of genes comprised by panMPS contributes to prostate cancer metastasis formation when copy numbers are altered.

For the outcome of triple negative breast cancer metastasis, univariate logistic regression of panMPS resulted in a significant odds ratio and AUC for the Montefiore cohort (OR 44.74, AUC 0.75, p=0.02) (Table 1B and FIG. 1). Percent genomic instability was not an independent predictor of metastasis. Because matching had been performed for the triple negative breast cancers, stage was also not a predictor of outcome.

For the outcome of lung adenocarcinoma metastasis, univariate logistic regression of panMPS resulted in a significant AUC for the MSKCC cohort (OR 3.45×10³, AUC 0.94, p=0.006) (Table 1C and FIG. 1). Because cases with advanced stage were selected for favorable outcome and cases with early stage were selected for unfavorable outcome, stage is thus not a valid predictor of metastasis.

Example 3. panMPS Predicts Metastasis-Free Survival for Prostate Cancer, Triple Negative Breast Cancer and Lung Adenocarcinomas

As a continuous univariate predictor through a Cox model, panMPS was associated with prostate cancer metastasis-free survival in both the MSK (HR=5.4, p=0.0003, concordance index 0.74) and Duke (HR=3.4, p=0.03, concordance index 0.62) cohorts (Table 2A). In univariate Cox analysis of the MSK cohort, percent genomic instability was associated with metastasis-free survival (HR=1.11. p=3.3×10⁷, concordance index=0.67), as previously reported for this cohort (Hieronymus, H. et al., Proc Nad Acad Sci USA 111, 11139-44 (2014)); however, this variable did not reach statistical significance in the Duke cohort. Biopsy and pathological Gleason scores, preoperative PSA and pathological stage and combinations of these with panMPS were predictors of metastasis-free survival in Cox analysis of the MSK cohort only (Table 6).

As a continuous univariate predictor in a Cox model, panMPS was associated with triple negative breast cancer metastasis-free survival in the Montefiore cohort (HR=4.1, p=0.05, concordance index 0.60) (Table 2B). Stage was also an independent predictor (HR=3.2, p=0.03), whereas percent genomic instability was not.

As a continuous Cox model univariate predictor, panMPS was associated with lung adenocarcinoma metastasis-free survival in the MSKCC cohort (HR=6.6, p=0.02, concordance index 0.67) (Table 2C). Stage cannot be used as a predictor as explained above.

Example 4. panMPS is Associated with Overall Survival in Breast Cancer, Prostate Cancer and Lung Adenocarcinoma

Data about CNAs in primary cancers and their survival outcomes are available for a variety of cancer types from publically available datasets, including The Cancer Genome Atlas (TCGA) (Gao J. et al., Sci Signal 6:p11, 2013, Cerami E. et al., Cancer Discov, 2:401-4, 2012) and Metabric (Milioli H H. Et al., PLoS One, 10:e0129711, 2015). To examine general utility as a predictor of survival outcome, Kaplan Meier analysis of panMPS was applied to the TGCA prostate cancer, breast cancer, and lung adenocarcinoma cohorts and the Metabric breast cancer cohort. panMPS (median cut point) was observed to be significantly associated with overall survival in the Metabric breast cancer cohort (n=1,980, p=4.8×10⁻⁰⁸) and in three TCGA cohorts (breast: n=1054, p=0.015, prostate: n=483, p=0.015, and lung adenocarcinoma: n=482, p=0.025; FIG. 2), providing evidence that panMPS is a predictor not only of metastasis, but also survival. Metastasis-free survival data were not available for these cohorts.

Example 5. panMPS is Elevated in Many Metastatic Cancer Cell Lines of Epithelial Origin

To test applicability in other cancer types, genomic instability and panMPS were evaluated in a set of 133 cell lines of different tissue origins from the Cancer Cell Line Encyclopedia (CCLE). All cell lines were reported to be from metastatic tumors. The median number of protein coding genes demonstrating CNAs ranged from 2091 for lymphoma to 6805 for pancreatic carcinoma and 6916 for stomach carcinoma, thereby confirming the high frequency of CNAs in metastases. By way of reference. the median number of genes demonstrating CNAs in a sample of clinical prostate cancer metastases was 3731. For metastatic cancer cell lines of epithelial origin, including breast, lung adenocarcinoma, pancreas and stomach, the frequency of CNAs was higher than those observed in prostate cancer metastases (p=0.04, 0.002, 3×10−4, 0.005, respectively), whereas for metastatic cell lines of non-epithelial origin, including lymphoid tissue, melanoma, and lung small cell, the frequency of unstable genes was similar to that observed for prostate cancer metastases. Despite the higher frequencies of CNAs among metastatic cells lines of epithelial origin, the MPS of these cell lines, including breast, lung adenocarcinoma, pancreas, large intestine and stomach, was similar to that observed in prostate cancer metastasis. Cell lines of non-epithelial origin had either comparable (melanoma) or lower MPS (lymphoid—p=8×10⁴, lung small cell—p=0.01) to those observed in clinical prostate cancer metastases. These findings extend the previous observation that the CNAs of cancer cell lines of a variety of origins display a specific CNA pattern (Pearlman A. et al., J Probab Stat, 2012:873570, 2012), suggesting that panMPS might serve as a predictor of metastatic outcome across multiple cancer types.

Example 6. MPS Genes are More Likely to have Known Roles in Promoting Metastasis or Predicting Metastatic Outcomes than Randomly Selected Genes

One way of gauging whether the MPS genes played a role in cancer metastasis beyond prostate and triple-negative breast cancers and lung adenocarcinomas was to identify Pubmed citations for these genes (Table 7). Further refinement of this search included metastatic functions such as cell viability, proliferation, invasion, and escape from apoptosis and for biomarker genes predictive of metastasis outcome when their copy number or expression is altered. Following guidelines for the functional interpretation of genes and their variants provided by the American College of Medical Genetics and Genomics (Richards S. et al., Genet Med, 17:405-24, 2015), the Association for Molecular Pathology (Rehm H L. Et al., N Engl J Med, 372:2235-42, 2015), and codified by the NIH-supported, Clinical Genome Resource (Strande N T., Am J Hum Genet, 100:895-906, 2017), each of the 366 MPS genes were annotated for literature reports. Statistical tests were then performed, first to compare MPS genes to random gene sets for metastatic functions and the second of protein coding gene sets that have known associations with metastasis functions, such as invasion, motility and escape from apoptosis when detached from matrix of origin, and chemokine activity, and for biomarker genes predictive of metastasis outcome when their copy number or expression is altered. The frequency of these citations was compared to the frequencies with which citations were observed for 100 random sets of 366 genes from the 18,638 protein coding genes that excluded overlapping MPS genes. Among the 366 MPS genes, 60 were found to have Pubmed citations for the search terms related to metastasis functions and metastasis biomarkers, whereas the range for the random sets was 26 to 69 (FIG. 2). In fact, only one random set had a larger number of genes cited (N=69) than the observed 60, indicating that both represented outliers of non-random gene sets based on current knowledge of annotated metastasis genes. In an alternative approach the 19,004 protein coding genes were annotated for whether they had known metastasis associations (“Metastasis ID,” Table 3, Table 8A), metastasis functions (“Metastasis functions,” Table 3, Table 8B) or whether they have been identified as biomarkers that were predictive of metastasis (“Metastasis biomarkers,” Table 3, Table 8C). Of 2463 metastasis ID genes, 112 overlapped with MPS genes (p=2.42×10⁻²⁰). Of 929 metastasis function genes, 40 overlapped with MPS genes (p=1.18×10⁻⁶). Of the 687 metastasis biomarker genes, 28 overlapped with MPS genes (p=0.0001). Thus, the MPS genes were enriched among gene sets with terms for metastasis function or metastasis biomarkers in the article.

Example 7. Elevated Z_(genes) Scores Provide Evidence for Potential Metastasis-Driver Genes

The MPS genes occur as singleton CNAs as well as in clumps that are distributed over 15 chromosomal arms (Table 7). The genes within a clump are likely to include both drivers that are directly associated with metastasis function and passengers that are indirectly associated with metastasis function, because of their proximity to a metastasis driver gene. For example, a clump index 26 on chromosome 8p21.3 includes the nine genes, PPP3CC, KIAA1967, BIN3, SORBS3, PDLIM2, RHOBTB2, SLC39A14, EGR3, and C8orf58 (Table 7). In this clump three of the 9 genes (EGR3, PDILMS, and RHOBTB2) overlapped with the gene sets, metastasis ID, metastasis functions and metastasis biomarkers. In addition to annotations, another way of gauging whether some of the MPS genes play a role as metastasis drivers is to compare the Z_(genes) scores within clumps (Pearlman. A. et al., J Probab Stat. 2012, 873570 (2012) and US Patent Publication No. 2014/0221229). The clumps of genes vary by breakpoints in individual cancer genomes and the CNAs of some genes in a clump will yield higher Z_(genes) scores by being overrepresented and in the right direction expected for metastasis, compared to cancer genomes that are not metastasis-prone. The range of Z_(genes) scores within a clump varied from 1.7 to over 10 with no apparent pattern of decay for the highest Z_(genes) score gene adjacent to those with the lowest Z_(genes) score (FIG. 3). Multiple genes within a clump had Pubmed annotations, which were not necessarily those with the highest Z_(genes) score. Some of the unannotated MPS genes with high Z_(genes) scores may also act as drivers of metastasis, but may not have been studied yet for functional roles (FIG. 5).

Other genes, including CDH13, CDH8, CDH2. CTD8, COL19A1, YWHAG, and ENOX1, do not belong to any clump. Both the Z_(genes) scores and the annotations of these genes suggest that they may act as drivers (Table 7). However, the functions of some of these genes may overlap with each other (e.g., the cadherin genes, CDH13, CDH8, CDH2). Thus, there may be some functional redundancy among the MPS genes and, as judged by Z_(genes) scores, genes are not equally predictive of the predisposition to metastasis. Yet, some of these genes have higher Z_(genes) scores suggesting that their contributions to metastasis are observed more frequently.

Example 8. High Z_(genes) Score Genes within Clumps Predict Outcomes

To test whether a reduced set of clumps could predict outcomes and produce similar values to those observed with panMPS, AUC and r² were calculated for simplified MPS versions that included genes with Z_(genes) score ≥4 (21 clumps) and Z_(genes) score ≥3 (43 clumps) or the highest Z_(genes) score gene within a clump. The results were compared to all 295 panMPS genes. The 21 and 43 clumps predicted AUC and r² almost as well panMPS, whether calculated for all genes exceeding the threshold or for only the gene with the highest Z_(genes) score (Table 9A and 9B). This result indicated that there was a hierarchy of clumps with 21 clumps (Z_(genes) score ≥24) performing as well as 43 clumps (Z_(genes) score ≥3) capturing almost all of the contribution of the clump to AUC and r². These result also indicated a lead gene within a clump could capture almost all of the contribution of the clump to AUC and panMPS r².

CNAs are the result of chromosomal instability and are far more common than mutations in human cancers, including prostate, triple negative breast cancer and lung adenocarcinoma (Vogelstein, B. & Kinzler, K. W., Nat Med. 10, 789-99 (2004), Kandoth et al., Nature, 502:333-9, 2013). CNAs may occur randomly across the genome or may be favored by repeated structural elements, including Alu or LINE sequences (Aguilera et al., Annu Rev Genet., 47:1-32, 2013). Amplifications or deletions of genes may occur repeatedly within the same regions of genomes in populations of cancer cells within a tumor (Pearlman. A. et al., J Probab Stat. 2012, 873570 (2012), Shah et al. Nature. 486:395-9, 2012). This observation of specific CNA pattern enrichment is the basis for calculating Zgenes scores for specific genes within CNAs. In turn, MPS represents the sum of Zgenes scores, divided by the number of genes being summed. CNA burden alone (i.e. the frequency of chromosomal instability) was not an accurate predictor of outcome in most cohorts because it did not consider specific pattern nor functional contributions by specific metastatic genes.

This disclosure provides evidence that panMPS can be used as a predictor of metastasis and metastasis-free survival, not only in prostate cancer, as we have shown before (Pearlman, A. et al., J Probab Stat. 2012, 873570 (2012)), but also for triple negative breast cancer, other breast cancers, and lung adenocarcinoma and 133 CCLE metastasis cell lines of 8 different cancer origins. A panMPS was also able to predict overall survival in Metabric cohort of breast cancer and several large TCGA cohorts of prostate cancer, breast cancer and lung adenocarcinoma.

These observations fit a model of chromosomal rearrangements occurring in early tumorigenesis by punctuated bursts (Gao R. et al., Nat Genet 48:1119-30, 2016). Metastasis is driven by selection for rearrangements that promote invasion, escape from apoptosis and growth at distant sites (Nyugen D X. et al., Nat Rev Genet 8:341-52, 2007 PMID: 17440531). A study of mutated genes in multiple cancer types drew a similar conclusion that genes under positive selection, either in individual or multiple tumor sites, tend to display higher mutation frequencies above background (Kandoth et al., Nature, 502:333-9, 2013). However, large-scale targeted and whole genome sequence efforts have identified single nucleotide variants and short indels in a set of overlapping or related genes that account for carcinogenesis, but have not identified genes involved in metastasis (Kan Z. et al., Nature 466:869-73, 2010).

These CNAs occur on a segmental basis with multiple genes within a segment or clump being amplified or deleted. Within a clump, one or more genes could be drivers of metastasis (Kandoth et al., Nature, 502:333-9, 2013). The drivers showed elevated Zgenes scores and were annotated in the literature as having metastatic functions, including invasion, motility, escape from apoptosis when detached from matrix of origin, and chemokine activity. Other genes with elevated Zgenes scores, but no annotations, may also represent drivers whose functions have not yet been identified. However, the remainder of the genes may be passengers that are carried along with the CNA events. Not all of the drivers are required for predicting risk of metastasis. Testing only genes with the highest Zgenes score within a clump may capture most, if not all of the metastatic risk, reflected by the panMPS. These genes with high Zgenes score may act as proxies for all of the genes within the clump.

Based on the hypergeometric analysis, the MPS genes indeed represent a subset of all metastatic genes, specifically those that can be readily identified by CNA analysis. Other metastatic genes would not be readily detected as they are not subject to CNA events and may need to be detected by other molecular methods, such as sequencing.

Analyzing these genes in patient samples may be required to improve the accuracy of predicting metastasis—although the current study suggests that as few as 33 genes with high Zgenes score may be sufficient for many clinical applications.

The availability of a panMPS-based diagnostic tool may contribute to clinical care. Collectively, lung, breast and prostate cancer account for ˜676,000 or 40% of newly diagnosed cancer cases and ˜226,000 or 39% of cancer deaths in the United States each year (Siegel R L. et al., CA Cancer J Clin, 65:5-29, 2015). Currently, there are no clinical tests in common use for prediction of outcomes in triple negative breast cancer or lung adenocarcinoma. Future studies will assess the accuracy of panMPS derived from surgical specimens and biopsies for predicting outcomes of these diseases.

Having a test that would accurately predict across cancer-types which patients are likely to develop metastases would be extremely useful. For example, panMPS could improve the clinical management of men with prostate cancer. Men with early-stage disease and low-risk profiles would be candidates for active surveillance that might safely preserve quality of life by helping them to avoid erectile dysfunction and urinary incontinence that may occur in up to 50% of treated patients (Cooperberg et al., J Nal Cancer Inst 101:878-87, 2009, Paris P L. et al., Clinical cancer research, 16:195-202, 2010). Men with early-stage disease and high-risk profiles might benefit from aggressive treatment (Pound C R. et al., The Urologic clinics of North America 24:395-406, 1997). Men with higher-risk disease who underwent initial surgery might benefit from adjuvant radiation therapy (Thompson I M., The Journal of urology 181:956-62, 2009). Notably, the accuracy of combined panMPS and pre-operative PSA appears to be similar to the various RNA expression profile tests plus clinical predictors for use as a post-surgical tool (Table 10A-10C). These tests, Genomic Prostate Score (GPS) (Cullen J. et al., European Urology, 68:123-31, 2015 PMID: 25465337., Klein E A. et al., European Urology, 66:550-60, 2014), Cell Cycle Progression Score (CCPS) (Cuzick J. et al., The Lancet Oncology 12:245-55, 2011), and Genomic Classifier (GC) (Ross A E et al., Prostate Cancer Prostatic Dis., 17:64-9, 2014; Cooperberg M R et al. European Urology 67:326-33, 2015; Erho N et al., PLoS One, 8:e66855, 2013 Karnes R J. et al., J Urol. 190:2047-53, 2013; 4097302: Den R B et al., Int J Radiat Oncol Biol Phys. 89:103846, 2014), measure the altered expression of mostly non-overlapping sets of genes that have not been demonstrated to play a direct role with the biological events of prostate cancer progression and metastasis. As with panMPS, the accuracy of these tests was improved by the addition of clinical and pathological predictors, both as univariate predictors or as captured by the Cancer of the Prostate Risk Assessment (CAPRA-S) score (Cooperberg M R et al., Cancer, 117:503946, 2011; 3170662; Greene K L et al., The Journal of Urology 171:2255-9, 2004), and the Stephenson nomogram (Brockman J A. et al., Eur Urol, 67:1160-7, 2015). Although Oncotype DX and Prosigna are two RNA expression profile tests in common use for prognostic prediction of breast cancer, their use is limited to estrogen receptor positive breast cancer (Nielsen T. et al., BMC Cancer. 14:177, 2014: Kaklamani V., Expert Rev Mol Diagn., 6:803-9, 2006).

TABLE 1A Univariate logistic regression model of panMPS predicts progression to metastasis for prostate cancer Cohort MSK prostate cancer (n = 182, mPT = 25, iPT = 157) Duke prostate cancer (n = 61, mPT = 37, iPT = 24) Variable Odds Ratio P 95% CI AUC Odds Ratio P 95% CI AUC panMPS 6.01 0.001 2.21 to 17.89 0.71 11.39 0.004 2.39 to 70.36 0.72

TABLE 1B Univariate logistic regression model of panMPS predicts progression to metastasis for triple negative breast cancer Montefiore triple negative breast cancer cohort (n = 41, mBC = 28, iBC = 13) Variable Odds Ratio P 95% CI AUC panMPS 44.74 0.02 2.91 to 1927.9 0.75

TABLE 1C Univariate logistic regression model of panMPS predicts progression to metastasis for lung adenocarcinoma MSK lung adenocarcinoma cohort (n = 33, mLA = 23, iLA = 10) Variable Odds Ratio P 95% CI AUC panMPS 3.45 × 10³ 0.006 41.5 to 1.26 × 10⁷ 0.94

TABLE 2A Univariate Cox proportional hazards model of panMPS predicts metastasis-free survival for prostate cancer Cohort MSK prostate cancer (n = 222, mPT = 25, iPT = 197) Duke prostate cancer (n = 76, mPT = 37, iPT = 39) Variable Hazard Ratio 95% CI Conc-indx P Hazard Ratio 95% CI Conc-indx P panMPS 5.42 2.18 to 13.49 0.74 0.0003 3.4 1.15 to 10.12 0.62 0.03

TABLE 2B Univariate Cox proportional hazards model of panMPS predicts metastasis-free survival for triple negative breast cancer Montefiore triple negative breast cancer cohort (n = 41, mBC = 28, iBC = 13) Variable Hazard Ratio 95% CI Conc-indx P panMPS 4.1 1.03 to 16.04 0.60 0.05

TABLE 2C Cox proportional hazards model of panMPS predicts metastasis-free survival for lung adenocarcinoma MSK lung adenocarcinoma (n = 33, mLA = 23, iLA = 10) Variable Hazard Ratio 95% CI Conc-indx P panMPS 6.57 1.31 to 33.04 0.67 0.02

TABLE 3 Hypergeometric analysis of MPS genes versus in silico gene sets for metastasis biomarker and metastasis function reviewed by cellular assays. Metastasis ID and chemokine ID terms in article title or abstract. Gene Set Overlap Gene set size Overlap % P Metastasis biomarkers 28 687 4.08 0.0001 Metastasis function 40 929 4.31 1.18 × 10⁻⁶  Metasiasis ID 112 2463 4.55 2.42 × 10⁻²⁰ Chemokine ID 65 3126 2.08 0.04 

TABLE 4 Left and Center: Logistic regression and Cox proportional hazards models predict progression to metastasis for full set (variable number by cohort) and panMPS (295) genes. Right: Linear regression model predicting correlation (r²) between MPS and panMPS. Linear Logistic Regression Cox Regression Regression Cohort Variables Odds Ratio P 95% CI AUC Hazard Ratio 95% CI Conc-Index P r² MSK_Prostate MPS 5.39 0.001 2.03 to 0.69 4.85 2.00 to 0.72 0.0005 0.97 (320 genes) 15.49 11.77 panMPS 6.01 0.001 2.21 to 0.71 5.42 2.18 to 0.74 0.0003 0.97 17.69 13.49 Duke_Prostate MPS 10.99 0.004 2.36 to 0.72 3.54 1.20 to 0.62 0.02 0.99 (351 genes) 65.88 10.44 panMPS 11.39 0.004 2.39 to 0.72 3.41 1.15 to 0.62 0.03 0.97 70.36 10.12 Montefiore_TNBC MPS 44.36 0.02 2.87 to 0.75 4.01 1.04 to 0.59 0.04 0.99 (352 genes) 2005.4 15.44 panMPS 44.74 0.02 2.91 to 0.75 4.06 1.03 to 0.59 0.05 0.96 1927.9 16.04 MSK_Lung MPS 3.78 × 10³ 0.006 42.79 to 0.94 4.55 1.04 to 0.65 0.04 0.96 (353 genes) 1.04 × 10⁷ 20.63 panMPS 3.45 × 10³ 0.006 41.5 0.94 6.57 1.31 to 0.67 0.02 0.96 to1.25 × 10⁷ 33.04

TABLE 5 Logistic regression models predicting progression to metastasis for prostate cancer based on panMPS and clinical variables Cohort MSK Prostate CA (n = 182, mPT = 25, iPT = 157) Duke Prostate CA (n = 61, mPT = 37, iPT = 24) Variable Odds Ratio P 95% CI AUC Odds Ratio P 95% CI AUC Univariate panMPS 5.98 0.001 2.12 to 18.57 0.7 11.84 0.002 2.78 to 67.71 0.75 Preop PSA 1.06 0.02 1.02 to 1.11 0.66 1.1 0.08 1.01 to 1.21 0.61 Biopsy Gleason 3.82 0.02 1.21 to 11.10 0.59 3.86 0.08 0.89 to 27.84 0.59 Clinical Stage 2.3 0.06 0.98 to 5.59 0.6 4 0.1 0.86 to 28.88 0.61 Path Gleason 68  1.3 × 10⁻¹⁰ 20.51 to 280.1 0.81 7.5 0.01 1.83 to 51.3 0.66 Path Stage 5.19 0.001 2.12 to 14.08 0.7 0.47 0.23 0.13 to 1.63 0.57 % Genome Inst. 1.17 1.4 × 10⁻⁵ 1.09 to 1.26 0.74 1.04 0.12 1.00 to 1.12 0.8 Multivariate panMPS 4.09 0.01 1.38 to 13.19 0.75 14.32 0.003 2.7 to 103.6 0.78 Preop PSA 1.04 0.05 1.01 to 1.1 1.1 0.06 1.01 to 1.24 panMPS 5.09 0.003 1.6 to 15.54 0.73 6.06 0.06 2.4 to 70.4 0.68 Biopsy Gleason 2.32 0.15 0.69 to 7.17 1.18 0.88 1.03 to 47.04 panMPS 5.51 0.001 1.99 to 16.59 0.73 4.42 0.13 0.71 to 34.06 0.72 Clinical Stage 1.93 0.15 0.79 to 4.83 2.76 0.26 0.52 to 21.2 panMPS 1.5 0.55 0.39 to 5.88 0.86 7.45 0.03 1.4 to 49.38 0.77 Path Gleason 56.8 1.21 × 10⁻⁸ 15.57 to 263.14 4.83 0.06 1.1 to 34.44 panMPS 3.93 0.01 1.43 to 11.94 0.77 10.59 0.01 2.18 to 65.6 0.73 Path Stage 3.83 0.006 1.49 to 10.74 0.59 0.45 0.15 to 2.32 panMPS 1.79 0.32 0.59 to 5.97 0.75 8.45 0.03 1.41 to 62.2 0.73 % Genome Inst. 1.15 0.001 1.06 to 1.25 1.01 0.53 0.98 to 1.07 panMPS 1.49 0.52 0.45 to 5.39 0.8 9.93 0.02 1.47 to 85.45 0.78 Preop PSA 1.03 0.21 1.00 to 1.09 1.1 0.06 1.01 to 1.24 % Genome Inst. 1.14 0.004 1.05 to 1.25 1.02 0.5 0.98 to 1.08 panMPS 3.7 0.03 1.2 to 11.93 0.76 8.6 0.04 1.25 to 90.53 0.74 Biopsy Gleason 2.2 0.21 0.59 to 7.1 1.35 0.78 0.17 to 13.8 Preop PSA 1.04 0.05 1.01 to 1.09 1.11 0.09 1.01 to 1.28 panMPS 4.71 0.01 1.66 to 14.48 0.75 4.47 0.13 0.70 to 36.93 0.71 Biopsy Gleason 2.24 0.17 0.66 to 6.97 0.93 0.95 0.12 to 8.55 Clinical Stage 1.88 0.17 0.77 to 4.76 2.8 0.26 0.51 to 22.16 panMPS 1.29 0.71 0.34 to 4.99 0.85 6.88 0.03 1.27 to 45.95 0.77 Path Gleason 47.21 8.69 × 10⁻⁸ 12.71 to 224.2 4.91 0.06 1.08 to 35.13 Path Stage 2.87 0.08 0.87 to 9.88 0.56 0.42 1.13 to 2.31 panMPS 3.56 0.03 1.16 to 11.62 0.78 6.97 0.04 0.94 to 77.9 0.76 Biopsy Gleason 2.15 0.22 0.59 to 6.97 1.07 0.08 0.11 to 11.94 Clinical Stage 1.41 0.48 0.54 to 3.71 2.73 0.46 0.46 to 22.54 Preop PSA 1.04 0.07 1.01 to 1.08 1.11 0.29 1.01 to 1.29 panMPS 3.5 0.03 1.16 to 11.2 0.79 5.68 0.13 0.66 to 68.5 0.76 Biopsy Gleason 2.2 0.22 0.60 to 7.51 1.34 0.82 0.12 to 31.9 Clinical Stage 1.37 0.52 0.52 to 3.61 2.39 0.37 0.38 to 20.3 Preop PSA 1.04 0.06 1.01 to 1.09 1.1 0.13 0.99 to 1.27 Age 0.51 0.35 0.13 to 2.49 7.85 × 10⁵ 0.99 3.85 × 10^(−10.4) to NA

TABLE 6 Cox proportional hazards model of panMPS and its association with metastasis- free survival for prostate cancer based on panMPS and clinical variables Cohort MSK Prostate CA (n = 222, mPT = 25, iPT = 197) Duke Prostate CA (n = 76, mPT = 37, iPT = 39) Variables Hazard Ratio 95% CI Conc-indx P Hazard Ratio 95% CI Conc-indx P Univariate panMPS 4.2 1.67 to 10.4 0.7 0.002 3.9 1.48 to 10.4 0.63 0.01 Preop PSA 1.01 1.00 to 1.01 0.63 7.60 × 10⁻⁵ 1 0.97 to 1.03 0.51 0.96 Biopsy Gleason 3.11 1.24 to 7.83 0.73 0.02 1.63 0.71 to 3.72 0.65 0.25 Clinical Stage 1.75 0.78 to 3.91 0.65 0.17 0.48 0.21 to 1.09 0.64 0.06 Path Gleason 17.34 7.63 to 39.4 0.97  9.90 × 10⁻¹² 1.67 0.84 to 3.34 0.71 0.14 Path Stage 3.99 1.67 to 9.58 0.82 0.002 0.61 0.23 to 1.57 0.57 0.3 % Genome Inst. 1.11 1.07 to 1.16 0.67 3.30 × 10⁻⁷ 1.01 0.99 to 1.02 0.66 0.2 Multivariate panMPS 4.31 1.72 to 10.8 0.74 0.002 3.52 1.18 to 10.5 0.71 0.02 Preop PSA 1.01 1.00 to 1.01 0.0002 0.99 1.02 to 1.12 0.7 panMPS 3.77 1.49 to 9.51 0.72 0.005 3.13 1.06 to 9.29 0.66 0.04 Biopsy Gleason 2.18 0.83 to 5.69 0.1 1.86 0.88 to 3.93 0.1 panMPS 4.59 1.83 to 11.6 0.71 0.001 2.25 0.62 to 8.17 0.6 0.22 Clinical Stage 1.81 0.81 to 4.03 0.15 1.86 0.79 to 4.34 0.15 panMPS 1.79 0.69 to 4.65 0.86 0.23 2.97 0.94 to 9.41 0.64 0.06 Path Gleason 14.34 5.96 to 34.5 2.74 × 10⁻⁹ 1.29 0.62 to 2.69 0.5 panMPS 2.96 1.19 to 7.33 0.76 0.02 3.19 1.05 to 9.64 0.62 0.04 Path Stage 3.03 1.22 to 7.55 0.02 0.73 0.27 to 1.91 0.5 panMPS 1.37 0.47 to 3.97 0.71 0.56 3.26 1.08 to 9.8 0.62 0.04 % Genome Inst. 1.1 1.04 to 1.16 0.001 1.01 0.99 to 1.02 0.32 panMPS 1.29 0.44 to 3.85 0.73 0.64 3.35 1.1 to 10.17 0.62 0.03 Preop PSA 1.01 1.00 to 1.01 0.0001 0.99 0.97 to 1.02 0.77 % Genome Inst. 1.09 1.04 to 1.16 0.001 1.01 0.99 to 1.02 0.35 panMPS 3.69 1.44 to 9.47 0.76 0.01 2.75 0.78 to 9.64 0.67 0.11 Biopsy Gleason 2.3 0.86 to 5.94 0.09 1.19 0.49 to 2.92 0.69 Prep PSA 1.01 1.00 to 1.01 0.0001 1.06 1.01 to 1.11 0.03 panMPS 4.07 1.58 to 10.5 0.74 0.01 1.96 0.53 to 7.23 0.6 0.31 Biopsy Gleason 2.09 0.81 to 5.42 0.13 1.69 0.72 to 3.97 0.23 Clinical Stage 1.76 0.78 to 3.94 0.17 2.02 0.84 to 4.85 0.11 panMPS 1.79 0.71 to 4.51 0.86 0.22 2.67 0.56 to 7.6 0.64 0.1 Path Gleason 11.98 4.98 to 28.8 2.91 × 10⁻⁸ 1.35 0.49 to 3.14 0.44 Path Stage 2.04 0.83 to 5.06 0.12 1.91 0.78 to 4.64 0.46 panMPS 3.95 1.51 to 10.3 0.76 0.01 2.06 0.56 to 7.61 0.65 0.28 Biopsy Gleason 2.19 0.84 to 5.72 0.11 1.25 0.49 to 3.14 0.63 Clinical Stage 1.57 0.68 to 3.58 0.29 1.91 0.78 to 4.64 0.15 Preop PSA 1.01 1.00 to 1.01 0.001 1.05 1.01 to 1.11 0.04 panMPS 3.95 1.49 to 10.5 0.76 0.01 1.73 0.46 to 6.55 0.66 0.42 Biopsy Gleason 2.21 0.84 to 5.76 0.11 1.58 0.59 to 3.92 0.37 Clinical Stage 1.56 0.68 to 3.6 0.29 1.68 0.66 to 4.29 0.27 Preop PSA 1.01 1.00 to 1.01 0.001 1.04 0.99 to 1.11 0.13 Age 0.89 0.26 to 3.09 0.86 8.31 × 10⁷ 0 to Inf 0.99

TABLE 7 Clump analysis of genes, including Z_(genes) score, clump index, number of genes in clump and PubMed ID for metastasis function annotations, metastasis predictive biomarkers and metastasis in the article Metastasis No. of Metastasis Predictive Z_(genes) clump genes in Function Biomarkers Metastasis Gene score index clump PubMed ID PubMed ID PubMed ID ACTL8 1.9 1 2 23592437 ARHGEF10L 2.1 1 2 LEPREL1 2.6 2 2 24319452 TP63 3.0 2 2 21760596, 15761962, 19142959, 24488880 23913939 26208975 GLRB 2.7 3 2 GRIA2 2.3 3 2 16953328 CCDC125 2.0 4 7 CDK7 2.7 4 7 23393140, 25117707 25490451, 25820824 CENPH 1.9 4 7 22999412 MARVELD2 3.0 4 7 MRPS36 2.6 4 7 RAD17 2.6 4 7 TAF9 2.6 4 7 EPHA7 1.8 5 2 16007213 MAP3K7 3.2 5 2 23370768, 17785553 25770290 ASCC3 1.8 6 2 SIM1 2.2 6 2 EPM2A 2.4 7 2 18824542 UTRN 2.3 7 2 C6orf118 2.8 8 2 PDE10A 4.7 8 2 CLIP2 3.1 9 4 EIF4H 2.0 9 4 LAT2 2.0 9 4 RFC2 1.8 9 4 MDH2 2.0 10 3 STYXL1 2.3 10 3 TMEM120A 1.7 10 3 PILRA 1.9 11 2 PILRB 2.9 11 2 ACTL6B 1.7 12 9 21136596 AGFG2 2.3 12 9 C7orf51 2.2 12 9 FBXO24 2.5 12 9 LRCH4 2.2 12 9 MOSPD3 2.3 12 9 PCOLCE 1.8 12 9 TFR2 2.6 12 9 TSC22D4 2.1 12 9 COPG2 3.1 13 7 CPA1 2.1 13 7 CPA2 2.1 13 7 CPA4 1.9 13 7 27073726 CPA5 2.8 13 7 MEST 3.2 13 7 23229728 TSGA14 9.4 13 7 CSMD1 4.6 14 2 18614856 MYOM2 2.1 14 2 ERI1 1.9 15 2 MFHAS1 3.3 15 2 MSRA 5.1 16 2 17784942 TNKS 4.0 16 2 C8orf16 2.2 17 2 MTMR9 1.9 17 2 GATA4 3.2 18 2 19509152 20222162 23239811, 24862985 NEIL2 2.7 18 2 C8orf79 2.9 19 2 DLC1 6.5 19 2 11118037 SGCZ 8.2 20 2 TUSC3 3.1 20 2 23404293, 23096450 24096664, 24435307, 25735931 MTMR7 3.7 21 4 MTUS1 3.6 21 4 19794912, 16650523 24299308, 25885343 PDGFRL 4.8 21 4 SLC7A2 4.1 21 4 ASAH1 7.1 22 2 23423838 PCM1 1.7 22 2 NAT2 3.3 23 3 PSD3 7.3 23 3 SH2D4A 2.9 23 3 FAM160B2 4.3 24 5 HR 2.7 24 5 LGI3 2.0 24 5 NUDT18 2.3 24 5 REEP4 2.5 24 5 BMP1 2.2 25 3 19723875 23584484 PHYHIP 2.2 25 3 POLR3D 2.7 25 3 BIN3 4.5 26 9 C8orf58 3.0 26 9 EGR3 2.0 26 9 23342064 KIAA1967 5.9 26 9 PDLIM2 2.9 26 9 23584482 24196835 PPP3CC 5.7 26 9 RHOBTB2 1.7 26 9 20930524, 15922864, 21801820 19173804, 19937980 SLC39A14 4.0 26 9 SORBS3 3.0 26 9 CHMP7 2.4 27 3 TNFRSF10A 2.2 27 3 TNFRSF10D 1.9 27 3 ENTPD4 2.7 28 2 LOXL2 1.9 28 2 25128648, 27008697 23030485 24014025, 24008674, 23971878, 23933800 CDCA2 2.0 29 3 23418564 17611626 EBF2 5.1 29 3 19671856 KCTD9 2.0 29 3 ADRA1A 3.9 30 7 21360568 24607827, 26276037 CHRNA2 3.5 30 7 DPYSL2 3.3 30 7 EPHX2 3.3 30 7 16456776 PTK2B 7.0 30 7 STMN4 3.3 30 7 TRIM35 2.6 30 7 C8orf80 3.6 31 3 ELP3 3.4 31 3 22740850 SCARA5 3.3 31 3 20038795, 22642751 24061576 HMBOX1 1.8 32 2 KIF13B 2.7 32 2 C8orf34 6.0 33 7 CPA6 3.8 33 7 NCOA2 5.6 33 7 25295534 PRDM14 4.7 33 7 21339739, 17942894, 25233927, 23690269 25635424 PREX2 7.5 33 7 22622578, 25151370, 25829446 SLCO5A1 9.1 33 7 SULF1 8.6 33 7 19780053, 19373441 21228115, 22653794 EYA1 3.4 34 6 24729159 KCNB2 6.8 34 6 LACTB2 2.6 34 6 MSC 2.0 34 6 TRPA1 2.3 34 6 24037916 XKR9 2.7 34 6 CRISPLD1 4.9 35 6 GDAP1 2.0 35 6 HNF4G 4.1 35 6 JPH1 6.0 35 6 PI15 3.0 35 6 ZFHX4 4.3 35 6 HEY1 3.0 36 2 23226563 STMN2 2.8 36 2 PAG1 2.0 37 2 21092590, 20388373, 21156787 21388951, 24675741 ZNF704 2.5 37 2 CNBD1 7.6 38 2 CNGB3 1.8 38 2 PTDSS1 2.5 39 2 SDC2 3.4 39 2 20863401, 19288017, 22745764 20683009 GRHL2 2.4 40 4 18752864, 23441166, 20938050, 26355710 23284647, 23814079, 24756056 NCALD 8.4 40 4 27027352 YWHAZ 2.2 40 4 20098429, 22912335 ZNF706 2.8 40 4 DPYS 3.2 41 3 LRP12 2.0 41 3 22138261, 14676824 ZFPM2 10.5 41 3 ANGPT1 2.4 42 2 20651738 RSPO2 1.8 42 2 21732367, 26416247 24476626 25769727 CSMD3 9.1 43 2 TRPS1 5.6 43 2 24709795, 16043716, 26183398 23762646, 26377811 MYC 4.2 44 3 20133671 15810077, 9012485 POU5F1B 2.9 44 3 TMEM75 3.5 44 3 ADCY8 8.5 45 5 19082487, 22419659 ASAP1 3.6 45 5 18519696, 24427349, 20154719 24788532 EFR3A 3.1 45 5 KCNQ3 6.0 45 5 OC90 1.9 45 5 PHF20L1 2.8 46 5 SLA 2.2 46 5 TG 3.8 46 5 TMEM71 2.9 46 5 WISP1 2.2 46 5 19078974, 175787808, 21109017, 20372786 21453685, 12865923 CDC42BPG 2.3 47 2 MEN1 2.1 47 2 ESD 2.6 48 3 21596165 HTR2A 3.3 48 3 LRCH1 2.4 48 3 DACH1 1.9 49 3 16980615 KLHL1 1.9 49 3 PCDH9 4.5 49 3 25172662 22300792, 25869928, 25979483 DDX19A 2.3 50 2 ST3GAL2 2.4 50 2 BCAR1 2.5 51 2 22476538 10539513, 15972849, 15448007, 21765937, 17192874, 22241677 23904007 CFDP1 3.0 51 2 ADAMTS18 3.5 52 4 18449690 25569086 21196270, 21047771, 24896365 CLEC3A 2.3 52 4 19173304 NUDT7 2.2 52 4 WWOX 9.3 52 4 14695174, 15073846, 18487009, 16360296, 23824713 17289881, 21731849 BCMO1 6.5 53 7 23803888 C16orf46 2.2 53 7 GAN 5.1 53 7 GCSH 1.9 53 7 HSD17B2 2.6 53 7 25929810 PKD1L2 6.9 53 7 PLCG2 5.6 53 7 HSDL1 2.0 54 3 LRRC50 2.4 54 3 MBTPS1 2.7 54 3 ATP2C2 3.6 55 3 KIAA1609 1.9 55 3 WFDC1 2.3 55 3 18842679, 10967136, 19468830 12032731, 15305341 CRISPLD2 5.4 56 5 KIAA0513 2.1 56 5 KLHL36 1.8 56 5 USP10 2.3 56 5 24332849, 16773218 24343337 25168367 ZDHHC7 2.5 56 5 C16orf74 2.3 57 8 21203532 COX4I1 2.6 57 8 COX4NB 2.5 57 8 FOXF1 2.2 57 8 24186199 23103611 20145151, 20587515, 23864317 GINS2 2.1 57 8 21082043, 24137407, 24273454 25348432 IRF8 2.5 57 8 23308054 24091328 17409439, 19074829, 24175153 KIAA0182 2.0 57 8 MTHFSD 2.4 57 8 BANP 5.9 58 13 17668048, 20709157, 25086032 18981184, 18822384 C16ORF85 2.1 58 13 CA5A 6.4 58 13 CYBA 2.9 58 13 IL17C 1.8 58 13 JPH3 4.8 58 13 KLHDC4 2.5 58 13 27030985 MVD 2.3 58 13 RNF166 2.2 58 13 SLC7A5 4.7 58 13 21439283 23981989, 26244545 SNAI3 2.4 58 13 ZC3H18 2.1 58 13 ZFPM1 2.5 58 13 CDT1 2.0 59 2 26408331 21159650 FAM38A 2.7 59 2 22792288 CBFA2T3 1.9 60 3 12183414 25749032 GALNS 2.3 60 3 TRAPPC2L 1.9 60 3 ANKRD11 6.7 61 2 18840648 21986947 CDH15 1.9 61 2 9615235 FANCA 1.9 62 4 SPIRE2 1.7 62 4 TCF25 2.1 62 4 TUBB3 2.6 62 4 25414139 24928347 20534991, 24053422 AFG3L1 2.3 63 2 DEF8 1.9 63 2 DHX58 6.9 64 5 HSPB9 2.9 64 5 KAT2A 3.2 64 5 KCNH4 3.8 64 5 RAB5C 3.5 64 5 ASPSCR1 1.8 65 2 NOTUM 2.7 65 2 DUS1L 2.3 66 2 FASN 3.0 66 2 18770866, 17882277 22266115, 22892389 DTNA 2.2 67 2 NOL4 3.9 67 2 C19orf57 2.8 68 2 CC2D1A 4.0 68 2 AR 4.9 69 4 7541709, 7723794, 8604394 11325816, EDA2R 2.0 69 4 HEPH 1.8 69 4 OPHN1 5.8 69 4 ALCAM 2.5 NA 1 16204050, 15509676, 9502422, 15140234 10702391 15986133, 16024937, 11206637, 18202807 ANXA13 2.1 NA 1 22294041 22559327 ARHGEF10 2.9 NA 1 21412932 ARHGEF5 2.7 NA 1 21525037 ATP6V1C1 2.4 NA 1 24155651, 20404513 15558013, 24454753 19885577, 18638373, 19424568, 17467328 BFSP2 2.4 NA 1 BLK 2.1 NA 1 BOD1L 2.4 NA 1 C13orf23 2.2 NA 1 C16orf80 2.2 NA 1 CCDC25 4.4 NA 1 22202459 CD226 3.3 NA 1 24468679 20008292 CDH13 10.9 NA 1 11389090, 12067979, 16807071, 15245595, 20642860 CDH17 2.8 NA 1 19676131, 23326130, 20568120, 22904132 23298905, 23604127, 23554857 CDH2 3.4 NA 1 19190132 20848731 CDH8 3.7 NA 1 CDYL2 2.5 NA 1 CLCNKB 2.0 NA 1 CLDN3 2.6 NA 1 19208807 CNGB1 1.8 NA 1 CNTNAP4 3.2 NA 1 COL11A1 1.9 NA 1 11375892, 19112599, 21047417 COL12A1 1.8 NA 1 21462330 COL19A1 3.4 NA 1 COL21A1 1.8 NA 1 CTNNA2 1.8 NA 1 24100690 CTSB 2.8 NA 1 16707449, 20133781 CYP7B1 1.7 NA 1 17639508 DCC 6.6 NA 1 26345965  9387266 DCHS2 2.8 NA 1 24898286 DGKG 1.9 NA 1 DIAPH3 3.3 NA 1 22593025 DLGAP2 2.2 NA 1 DNAH2 1.8 NA 1 DOCK5 5.4 NA 1 DPYD 2.9 NA 1 ENOX1 5.6 NA 1 21055930 EPO 2.0 NA 1 24497137 FBXL18 1.9 NA 1 FBXL4 1.7 NA 1 FSTL5 2.2 NA 1 GABRA2 2.3 NA 1 GAS8 2.9 NA 1 GHDC 1.8 NA 1 GIGYF1 2.7 NA 1 GLG1 2.1 NA 1 25301730 19148506 GPC5 2.1 NA 1 23962560 26631038 24260047, 25093697, 25818666, 26098560 GRID2 5.1 NA 1 GRK5 2.4 NA 1 22099983, 24755472 GRM1 1.9 NA 1 18435704, 23065756, 24491800, 16040064 GYS2 2.8 NA 1 HIP1 4.4 NA 1 12163454 21697888 26595459 IMPA1 1.9 NA 1 IQCE 1.8 NA 1 KALRN 2.4 NA 1 KCNAB1 5.8 NA 1 KCTD8 2.8 NA 1 KIAA0196 2.6 NA 1 16130124 LPHN3 2.5 NA 1 23317273 LZTS1 2.0 NA 1 18559591 18686028, 11410489, 24466374 23695671, 24525428 MACROD1 4.8 NA 1 MDGA2 2.8 NA 1 ME1 2.5 NA 1 25753478 MECOM 2.0 NA 1 MEF2C 2.3 NA 1 19584403 MEIS2 3.9 NA 1 MEPCE 2.1 NA 1 MLYCD 2.4 NA 1 MMP16 3.5 NA 1 21600596 MTDH 1.9 NA 1 19111877, 19723648, 21976539, 22031094, 21371176, 23851509 24099913 MTMR9 1.9 NA 1 MYLK 2.8 NA 1 15970650, 25179839 NALCN 2.2 NA 1 NECAB2 2.0 NA 1 NFAT5 2.3 NA 1 19011242, 22266867, 25152734, 25311085, 26299924 NIPAL2 1.9 NA 1 NKIRAS2 2.0 NA 1 NKX2-6 2.4 NA 1 NLGN4Y 2.4 NA 1 NRXN1 3.2 NA 1 NUS1 2.2 NA 1 PDS5B 2.0 NA 1 23850494 PKIA 3.3 NA 1 PLCB1 1.9 NA 1 26620550 PPM1L 2.0 NA 1 PPP2R5B 1.8 NA 1 PTK2 2.3 NA 1 14578863 RAB9A 3.7 NA 1 RALYL 2.8 NA 1 RCOR2 1.7 NA 1 RFX1 2.2 NA 1 RGS22 2.7 NA 1 21533872 26323264 RIMS2 6.0 NA 1 RNF40 2.1 NA 1 22155569 RPL7 2.3 NA 1 SF1 2.5 NA 1 18824866 SLC26A7 2.2 NA 1 SLC9A9 2.7 NA 1 25835977 SMARCB1 1.8 NA 1 15899790, 16528370, 17040295, 21057957, 24503755 STAG3 2.4 NA 1 STAU2 4.6 NA 1 STIP1 1.8 NA 1 24163084, 24488757 STK3 1.8 NA 1 STX1A 2.2 NA 1 TBC1D10B 1.8 NA 1 TBC1D22A 4.6 NA 1 TCEB1 1.8 NA 1 18844214 25676555 TFDP1 2.3 NA 1 14618416 26684807 19995430 TFE3 2.1 NA 1 11438465, 12459622, 19606011, 20154303, 20871214 TICAM2 1.8 NA 1 TOX 4.3 NA 1 TRDN 3.0 NA 1 UBE2CBP 2.8 NA 1 UBR5 2.2 NA 1 VPS13B 3.9 NA 1 VPS13C 1.8 NA 1 WDR59 2.1 NA 1 WDR7 2.0 NA 1 WWP2 1.8 NA 1 26662306 23938591, 26783238 XPO7 2.3 NA 1 YWHAG 2.7 NA 1 ZBTB20 1.8 NA 1 25311537 21702992 ZFAT 2.5 NA 1 ZFHX3 2.2 NA 1 ZHX2 2.6 NA 1 17447851 ZSWIM4 2.8 NA 1

TABLE 8A Genes in gene set for Metastasis ID SEPT9, DEC1, ABAT, ABCA13, ABCA2, ABCA3, ABCB1, ABCB11, ABCB5, ABCC10, ABCC2, ABCC3, ABCC5, ABCD1, ABCD3, ABCE1, ABCG1, ABCG2, ABCG4, ABHD11, ABHD4, ABI1, ABI2, ABL1, ABL2, ABR, ACACA, ACCS, ACE, ACE2, ACHE, ACP1, ACP5, ACP6, ACPT, ACR, ACRBP, ACSS2, ACTB, ACTG2, ACTN4, ADAM10, ADAM19, ADAM29, ADAM33, ADAM7, ADAM8, ADAM9, ADAMTS1, ADAMTS12, ADAMTS13, ADAMTS18, ADAMTS19, ADAMTS5, ADAMTS8, ADIPOQ, ADIPOR1, ADIPOR2, ADM, ADO, ADORA2B, ADRA2A, ADRB2, ADRBK2, ADRM1, AES, AFAP1, AFAP1L1, AFM, AFP, AGA, AGBL2, AGK, AGR2, AGR3, AGXT, AHNAK, AHR, AHSG, AIM1, AIM2, AKAP12, AKAP13, AKIRIN2, AKR1B10, AKR1C1, AKR1C3, AKT1, AKT2, AKT3, ALDH1A1, ALDH1A3, ALDH3A1, ALK, ALCAM, ALKBH5, ALOX5, AMN, AMOTL1, AMOTL2, ANG, ANGPT2, ANGPTL2, ANGPTL3, ANLN, ANKRD11, ANO1, ANO9, ANP32A, ANTXR1, ANXA1, ANXA11, ANXA2, ANXA5, ANXA7, APAF1, APC, APCS, API5, APLP2, APOA1, APOBEC3G, APOH, APP, APPL1, AQP1, AQP3, AQP5, AQP6, AQP9, AR, ARAF, AREG, ARF1, ARF6, ARFGAP1, ARG1, ARHGAP21, ARHGAP5, ARHGAP6, ARHGEF3, ARHGEF5, ARHGEF7, ARID1A, ARID2, ARID3B, ARID4A, ARID4B, ARL4C, ARMC3, ARNT, ARPC1B, ARRB1, ARRDC3, ASAP1, ASCL2, ASIP, ASL, ASPM, ASS1, ATAD2, ATF1, ATF3, ATF4, ATF5, ATF6, ATG10, ATG16L1, ATG4A, ATG5, ATIC, ATM, ATOH1, ATOH8, ATP11A, ATP4A, ATP5J, ATP6AP2, ATP6V1C1, ATP7B, ATR, ATRX, AURKA, AUTS2, AVEN, AXIN2, AZGP1, B3GALNT1, B3GNT3, B3GNT7, B4GALNT2, BACE1, BACH1, BAD, BAG1, BAG2, BAG3, BAIAP2L1, BAMBI, BARD1, BARX2, BATF2, BAX, BAZ2A, BCAM, BCAR1, BCAR3, BCAS2, BCAS3, BCAT1, BCL10, BCL2, BCL2L12, BCL2L2, BCL3, BCL6, BCL9, BCL9L, BCOR, BCORL1, BCR, BDKRB2, BDNF, BET1, BHMT, BID, BIK, BIN1, BIRC3, BIRC5, BIRC6, BLCAP, BLID, BMF, BMP1, BMP10, BMP3, BMP4, BMP6, BMP7, BMPER, BMPR1A, BNC1, BNIP3L, BOLL, BOP1, BPI, BPTF, BRCA1, BRCA2, BRCC3, BRD4, BRD8, BRE, BRF2, BRIP1, BRMS1, BRMS1L, BRSK2, BST2, BTBD7, BTC, BTG1, BTG2, BTG3, BTK, BTLA, BTRC, BUB1, BUB1B, BVES, C10orf10, C19orf48, C1orf61, C2orf40, C3, C5, C6, C6orf106, C7, C8orf4, C9, CA2, CA9, CACNA2D3, CACYBP, CAD, CADM1, CALU, CAMK2N1, CAMP, CAMSAP1, CANT1, CAPZA1, CARD10, CARM1, CARS, CASK, CASP4, CASP6, CASP8, CASR, CASS4, CAV1, CBL, CBX2, CBX4, CBX5, CBX7, CBX8, CCDC34, CDC6, CCDC67, CCDC8, CCL1, CCL11, CCL13, CCL14, CCL17, CCL18, CCL19, CCL2, CCL20, CCL21, CCL22, CCL4, CCL5, CCL7, CCL8, CCNA2, CCNB1, CCNE1, CCNG2, CCNH, CCNY, CCR1, CCR3, CCR4, CCR6, CCR7, CCR9, CCRL2, CCT2, CD109, CD14, CD163, CD163L1, CD164, CD1A, CD1C, CD1D, CD2, CD200, CD226, CD244, CD248, CD27, CD274, CD33, CD36, CD38, CD4, CD40, CD46, CD47, CD48, CD53, CD55, CD58, CD63, CD69, CD70, CD74, CD81, CD82, CD86, CD9, CD93, CD96, CD99, CDA, CDC14A, CDC20, CDC25A, CDC25B, CDC25C, CDC37, CDC42, CDC6, CDC7, CDC73, CDCA5, CDCA7L, CDCA8, CDCP1, CDH1, CDH13, CDH17, CDH2, CDH22, CDK2AP1, CDK3, CDK4, CDK5, CDK5RAP3, CDK6, CDK7, CDK8, CDKN1A, CDKN1C, CDKN2A, CDKN2B, CDKN3, CDT1, CDX1, CDX2, CEACAM1, CEACAM5, CEP55, CEP70, CES2, CFL1, CFTR, CGA, CHAD, CHAT, CHD1, CHD1L, CHD5, CHD8, CHEK1, CHEK2, CHGB, CHI3L1, CHL1, CHML, CHRM3, CHRNA1, CHRNA3, CHST11, CIAPIN1, CIITA, CISD2, CISH, CITED1, CITED2, CIZ1, CKAP2, CKAP4, CKB, CLC, CLCA1, CLCA2, CLCA4, CLDN10, CLDN11, CLDN16, CLDN3, CLEC3A, CLEC3B, CLEC5A, CLIC4, CLOCK, CLPTM1L, CLU, CMTM3, CMTM8, CNN3, CNOT7, CNTF, CNTN1, COIL, COL11A1, COL18A1, COL1A1, COL1A2, COL3A1, COL4A2, COL5A1, COL5A2, COL6A1, COMMD1, COMT, CORT, COTL1, COX7A2, CP, CPA4, CPE, CPEB4, CPM, CPNE3, CPOX, CPS1, CPSF2, CPT1A, CPZ, CR1, CRABP1, CRCT1, CREB1, CREB3, CREB3L1, CREB3L2, CREB5, CREBBP, CREBZF, CRH, CRHR1, CRHR2, CRIM1, CRISP3, CRK, CRKL, CRNN, CRP, CRTC1, CRTC3, CRX, CS, CSE1L, CSF1, CSF2, CSK, CSMD1, CSNK1A1, CSPG4, CST6, CST7, CTAG2, CTBP1, CTBP2, CTCF, CTCFL, CTGF, CTHRC1, CTLA4, CTNNA1, CTNNB1, CTNND1, CTTN, CUEDC2, UL4A, CUX1, CX3CL1, CX3CR1, CXCL1, CXCL10, CXCL11, CXCL12, CXCL13, CXCL14, CXCL17, CXCL2, CXCL3, CXCL5, CXCL6, CXCL9, CXCR4, CXCR5, CXCR6, CXXC4, CXXC5, CYB5A, CYB5D2, CYFIP1, CYHR1, CYLD, CYP17A1, CYP19A1, CYP1A1, CYP1B1, CYP24A1, CYP26A1, CYP27A1, CYP27B1, CYP2A6, CYP2B6, CYP2C8, CYP2E1, CYP2J2, CYP2R1, CYP39A1, CYP3A4, CYP3A43, CYP3A5, CYP4F8, CYR61, DAB1, DAB2, DAB2IP, DACH1, DACH2, DACT1, DACT2, DAND5, DAP, DAP3, DBF4, DBN1, DCC, DCK, DCLK1, DCN, DCT, DCTN1, DCUN1D1, DCX, DCXR, DDB2, DDC, DDIT3, DDR2, DDT, DDX1, DDX11, DDX20, DDX27, DDX43, DEDD, DEK, DEPDC1B, DES, DFNA5, DGCR6, DGCR6L, DGCR8, DHCR24, DHFR, DHRS7, DHX32, DIAPH1, DIAPH3, DICER1, DIO3, DIRAS1, DIRAS3, DIS3, DIXDC1, DKK1, DKK2, DLC1, DLD, DLEC1, DLG5, DLK1, DLK2, DLL4, DLX2, DLX5, DMGDH, DMP1, DNAJA1, DNAJB1, DNAJC13, DNM3, DNMT1, DNMT3A, DOCK1, DOCK2, DOCK3, DOCK4, DOCK5, DOCK8, DOT1L, DPF3, DPH3, DPP4, DPPA2, DPYD, DR1, DRD2, DSC1, DSG1, DSG3, DTX3L, DUOX2, DUSP1, DUSP4, DUSP6, DYRK1B, DYRK2, E2F1, E2F2, E2F3, E2F4, E2F5, E2F6, EBAG9, EBF2, EBP, ECD, ECH1, ECM1, ECT2, EDIL3, EDNRA, EDNRB, EEF1A2, EFEMP1, EFHD2, EFNA1, EFNA3, EFNB2, EGF, EGFL7, EGFR, EGR1, EGR3, EHD1, EHMT1, EI24, EIF3A, EIF3E, EIF3H, EIF3I, EIF4E, EIF5A2, EIF6, ELAC2, ELAVL1, ELF3, ELF5, ELMO2, ELP3, ELOVL6, EMILIN1, EMP2, EMX2, ENAH, ENG, ENO1, ENPP2, ENTPD5, EP300, EPAS1, EPB41L3, EPC1, EPCAM, EPHA1, EPHA2, EPHA3, EPHA4, EPHA6, EPHA7, EPHA8, EPHB2, EPHB3, EPHB4, EPHB6, EPHX2, EPO, EPS15, EPS8, EPSTI1, ERBB3, ERBB4, ERC1, ERCC1, ERCC2, ERCC3, ERCC5, ERG, ERGIC1, ERGIC3, ERP29, ESD, ESPL1, ESPN, ESR1, ESR2, ESRP1, ETS1, ETV1, ETV4, ETV5, ETV6, EVI5, EVL, EVX1, EWSR1, EXO1, EXT1, EXTL3, EYA1, EYA2, EYA4, EZH2, EZR, F10, F11, F2, F5, F8, F9, FABP1, FABP4, FABP5, FABP7, FADD, FAF1, FAIM2, FAM107A, FAM120A, FAM129B, FAM134B, FAM20C, FAM3B, FAM3C, FAM83D, FANCA, FANCC, FANCD2, FANCF, FAP, FAS, FASN, FASTKD2, FAT4, FBN1, FBN2, FBXL5, FBXO11, FBXO32, FBXO4, FBXO45, FBXW7, FCN2, FDPS, FECH, FEM1A, FER, FEV, FEZ1, FEZF1, FGD4, FGF1, FGF10, FGF14, FGF18, FGF2, FGF23, FGF3, FGF4, FGF5, FGF7, FGF8, FGF9, FGFBP1, FGFR1, FGFR2, FGFR3, FGFR4, FGG, FGR, FH, FHIT, FHL1, FHL2, FHOD1, FHOD3, FJX1, FKBP14, FKBPL, FLI1, FLNA, FLOT2, FLT1, FLT3, FLT4, FMNL2, FMNL3, FN1, FNDC3B, FOSB, FOXA1, FOXA2, FOXC1, FOXC2, FOXD3, FOXE1, FOXF1, FOXF2, FOXG1, FOXH1, FOXJ1, FOXJ3, FOXL1, FOXL2, FOXM1, FOXO1, FOXO3, FOXO4, FOXP1, FOXP2, FOXP3, FOXQ1, FOXR2, FRAS1, FRAT1, FRMD4A, FRY, FRYL, FSCN1, FSHR, FST, FSTL1, FURIN, FUS, FUT3, FUT4, FUT5, FUT8, FXYD3, FXYD5, FXYD6, FYN, FZD1, FZD2, FZD5, FZD8, G3BP1, GAB1, GAB2, GABARAPL1, GABRP, GADD45A, GADD45G, GAK, GAL, GAL3ST2, GALC, GALNT14, GALNT2, GALNT3, GALNT9, GAN, GAS1, GAS6, GAS8, GAST, GATA2, GATA4, GATA5, GATA6, GBP1, GBP2, GBX2, GC, GCG, GCKR, GDF15, GDF2, GDF3, GDNF, GEM, GEMIN5, GFAP, GFI1, GGH, GHRH, GIP, GIPC1, GIT1, GJA3, GJB5, GKN1, GLA, GLB1, GLE1, GLI1, GLI2, GLIPR1, GLO1, GMDS, GNA13, GNA15, GNAI2, GNAI3, GNAQ, GNAS, GNE, GNG2, GNRH1, GOLPH3, GP2, GPC5, GPI, GPNMB, GPR171, GPR18, GPR32, GPR34, GPR39, GPR55, GPR87, GPRC5A, GPX2, GPX3, GRB14, GRB2, GRHL2, GRHL3, GRIN2A, GRK5, GRK6, GRM1, GRM4, GRM5, GRPR, GSC, GSN, GSPT1, GSTM3, GSTP1, GTSE1, GUCY2C, GUK1, H3F3A, HABP2, HACE1, HADHA, HAO2, HAPLN3, HAS1, HAS2, HAX1, HBD, HBEGF, HBP1, HCCS, HDAC1, HDAC2, HDAC4, HDAC6, HDAC7, HDAC8, HDGF, HECTD1, HECTD2, HELLS, HEPACAM, HERC5, HES1, HES5, HEXA, HEXIM1, HEY1, HFE, HGS, HHIP, HIF1A, HINT1, HIP1, HIPK1, HIPK2, HIRA, HJURP, HK1, HK3, HLTF, HMGA1, HMGA2, HMGB3, HMGCR, HMGCS2, HMGN1, HMGN5, HMMR, HN1, HNF1A, HNF4A, HNRNPA2B1, HOMER1, HOOK1, HOPX, HOXA1, HOXA11, HOXA13, HOXA5, HOXA9, HOXB2, HOXB9, HOXC11, HPD, HPGD, HPR, HPSE, HR, HRG, HS3ST2, HSD17B2, HSD3B1, HSF1, HSP90B1, HSPA14, HSPA2, HSPA9, HSPB8, HTATIP2, HTRA1, HTRA2, HTRA3, HTT, HUNK, HUWE1, HYOU1, IAPP, ICMT, ID1, ID2, ID3, ID4, IDH1, IDH2, IDO1, IER2, IFI27, IFIT2, IFIT3, IFNG, IGF1R, IGF2, IGF2BP1, IGF2BP2, IGF2BP3, IGFBP1, IGFBP2, IGFBP3, IGFBP5, IGFBP7, IGFBPL1, IKBKB, IKZF1, IL10, IL13, IL17A, IL17F, IL18, IL1A, IL1R1, IL23R, IL24, IL33, IL4, IL6R, IL7, ILK, IMP3, IMPACT, INA, ING1, ING2, ING3, ING5, INHBA, INSIG2, INSM1, IQGAP1, IQGAP2, IRAK1, IRF8, IRX2, IRX5, ITGA2, ITGA3, ITGA5, ITGA7, ITGA8, ITGA9, ITGAV, ITGB1, ITGB3, ITGB4, ITGB8, ITGBL1, ITIH5, JAG1, JAG2, JAK1, JAK2, JAK3, JAZF1, JMJD6, JUN, KAT2A, KCNJ1, KCNK9, KCNMA1, KCNQ1, KCNRG, KDM1A, KDM2A, KDM3A, KDM4A, KDM4B, KDM4C, KDM5B, KDM5C, KDM6A, KDR, KEAP1, KIAA0101, KIF11, KIF14, KIF15, KIF18A, KIF1B, KIF26B, KIF2A, KIF3A, KIF3C, KIF5B, KIFC1, KIN, KIR2DL4, KISS1, KIT, KITLG, KL, KLB, KLF12, KLF15, KLF17, KLF2, KLF4, KLF5, KLF6, KLHDC4, KLK10, KLK14, KLK15, KLK3, KLK7, KLK8, KLRG1, KMO, KPNA2, KPNB1, KRAS, KRT19, KRT20, KRT7, KY, LAMA4, LAMA5, LAMB1, LAMB3, LAMB4, LAMC1, LAMC2, LAMP1, LAMP2, LAMP3, LAP3, LAPTM4B, LARP1, LARP7, LARS, LASP1, LAT, LATS1, LATS2, LBH, LBX1, LCK, LCT, LDB1, LEMD3, LEP, LEPREL1, LETM1, LFNG, LGALS3, LGALS3BP, LGALS9, LGI4, LGR5, LHCGR, LIF, LIFR, LIG4, LILRB1, LILRB2, LIMD2, LIMK2, LIN28B, LMNA, LMO2, LMO4, LMO7, LMX1B, LOX, LOXL2, LPAR1, LPCAT1, LPHN3, LPIN2, LPP, LRG1, LRP1, LRP1B, LRP5, LRP6, LRP8, LRPPRC, LRRC3B, LRRC4, LRRFIP1, LSAMP, LSM1, LSP1, LTBP4, LXN, LY75, LYAR, LYN, LZTFL1, LZTS1, MACROD2, MADD, MAGEA1, MAGEC2, MAGED4B, MAGI1, MAK, MAL, MAL2, MALL, MALT1, MAML1, MAML2, MAOA, MAP1B, MAP1S, MAP2, MAP2K1, MAP2K4, MAP3K1, MAP3K2, MAP3K7, MAP3K8, MAP3K9, MAP4K3, MAP4K4, MAPK1, MAPK8, MAPKAPK2, MAPT, MARCKS, MARCO, MARK4, MARVELD3, MAS1, MAT2A, MAT2B, MAX, MB, MBD1, MBD2, MBD4, MBP, MCC, MCM2, MCM4, MCRS1, MDM4, ME1, MED1, MED12, MED19, MED27, MEF2C, MEF2D, MEIS1, MEMO1, MEN1, MEST, MET, METTL13, MFAP3L, MFSD2A, MGA, MGAT1, MGAT3, MGMT, MGST1, MIA, MIB1, MICAL2, MIF, MINA, MIP, MITF, MKL1, MLF2, MLN, MME, MMP10, MMP11, MMP12, MMP13, MMP14, MMP16, MMP28, MMP7, MMP9, MNT, MOBP, MOS, MOV10, MPI, MPL, MPO, MPZL1, MRC2, MSC, MSH3, MSH6, MSMB, MSN, MSRA, MST1R, MSX2, MT3, MT4, MTA1, MTA2, MTA3, MTAP, MTBP, MTDH, MTHFD2, MTHFR, MTMR3, MTOR, MTRR, MTSS1, MTUS1, MUC13, MUC16, MUC17, MUC2, MUC20, MUC4, MUC7, MUM1, MUSK, MUT, MUTYH, MVD, MVP, MX1, MX2, MXD1, MXI1, MXRA5, MYBL2, MYC, MYCN, MYD88, MYEOV, MYH9, MYL9, MYLK, MYO5B, MYO9B, MZF1, NAB2, NAMPT, NAP1L1, NAT1, NAT2, NAV1, NBN, NCALD, NCK1, NCK2, NCL, NCOA1, NCOA2, NCOA3, NCOA5, NCOR1, NCOR2, NCSTN, NDC80, NDP, NDRG2, NDRG3, NDRG4, NDUFB6, NDUFB9, NDUFS6, NEB, NEDD1, NEDD4, NEDD4L, NEDD8, NEFL, NEIL1, NEIL2, NEK2, NEK6, NEK7, NES, NET1, NETO2, NEU3, NEUROD1, NF1, NFAT5, NFATC2, NFIB, NFKB1, NFKBIA, NGF, NGFR, NHS, NIPSNAP1, NISCH, NKD1, NKD2, NKTR, NLK, NLRP1, NLRP3, NME1, NME4, NME6, NMI, NMU, NNAT, NNT, NOB1, NOD1, NOD2, NODAL, NOG, NOP14, NOS1, NOS2, NOS3, NOTCH1, NOTCH3, NOTCH4, NOV, NOX1, NOX4, NPAS2, NPC1, NPL, NPM1, NPS, NPY, NPY1R, NQO2, NR0B1, NR1D1, NR1I2, NR1I3, NR2F1, NR2F2, NR3C2, NR4A2, NR4A3, NR5A2, NR6A1, NRAS, NRK, NRL, NT5E, NTRK1, NTRK3, NTS, NTSR1, NUAK1, NUCB2, NUCKS1, NUMB, NUP88, NUSAP1, OAT, ODAM, ODF4, OLA1, OLFM4, OLIG1, OLIG2, ONECUT2, ORAI1, ORAOV1, OSM, OSMR, OTC, OTP, OTUB1, OTUD3, P4HA1, P4HA2, PABPC1, PACRG, PADI4, PAFAH1B1, PAH, PAK2, PAK3, PAK4, PAK6, PALB2, PAM, PARD3, PARG, PARP1, PARVA, PARVB, PAX3, PAX4, PAX5, PAX6, PAX7, PAX8, PBK, PBRM1, PBX3, PC, PCBP1, PCBP2, PCDH10, PCDH9, PCK2, PCNA, PDC, PDCD4, PDCD5, PDCD6, PDCL3, PDF, PDGFB, PDGFRA, PDGFRB, PDIA3, PDK3, PDLIM2, PDLIM5, PDPN, PDSS2, PDX1, PEBP1, PEG10, PELP1, PER1, PER2, PERP, PFKFB2, PFKFB3, PFN2, PGC, PGF, PGK1, PGRMC2, PHF10, PHF20, PHF8, PHIP, PHLDA1, PHLPP1, PHLPP2, PHOX2B, PIAS1, PICK1, PIGF, PIGR, PIGS, PIEZO1, PIK3C2G, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R3, PIKFYVE, PIN1, PINK1, PIP4K2B, PIR, PITPNC1, PITX1, PITX2, PIWIL1, PIWIL2, PIWIL4, PKN1, PKP1, PKP2, PLA2G16, PLA2G7, PLAC1, PLAG1, PLAGL1, PLAU, PLAUR, PLCE1, PLCG1, PLD2, PLEKHA5, PLK1, PLOD2, PLS3, PLXDC1, PLXNA2, PMAIP1, PMEPA1, PML, PMP22, PMS2, PNLIPRP3, POLB, POLE, POLI, POLR2A, POMC, PON1, POSTN, POT1, POU2F1, POU3F2, POU3F3, PPA1, PPARG, PPM1A, PPM1B, PPM1D, PPM1F, PPM1H, PPP1CA, PPP1R13L, PPP1R3B, PPP2CA, PPP2R2C, PRAME, PRC1, PRDM10, PRDM14, PRDM5, PRDX1, PRDX4, PRDX6, PREP, PAG1, PTK2B, PREX2, PRICKLE1, PRKAA1, PRKAR1A, PRKCD, PRKCDBP, PRKCI, PRKCZ, PRKD1, PRKD2, PRKX, PRL, PRMT1, PRMT2, PRMT5, PRMT6, PRMT7, PRNP, PROK1, PROM1, PROX1, PRR15, PRSS3, PRUNE, PRUNE2, PRX, PSAT1, PSCA, PTBP2, PTCH1, PTEN, PTER, PTGIS, PTGS2, PTH, PTH1R, PTHLH, PTK6, PTK7, PTOV1, PTP4A1, PTP4A3, PTPN12, PTPN13, PTPN14, PTPN4, PTPRF, PTPRG, PTPRT, PTS, PTTG1IP, PTX3, PVR, PYY, QKI, QRFP, RAB11A, RAB14, RAB17, RAB1A, RAB22A, RAB25, RAB27B, RAB32, RAB3D, RAB40B, RAB40C, RAB5C, RABL3, RAC1, RAC2, RACGAP1, RAD18, RAD21, RAD50, RAD51, RAD52, RAD54B, RAF1, RAI2, RALA, RALB, RALBP1, RALY, RAMP3, RAN, RANGAP1, RAP1A, RAP1B, RAP1GAP, RAP2A, RAP2B, RAPGEF2, RAPH1, RARB, RARRES1, RASA1, RASAL1, RASAL2, RASGRF1, RASGRF2, RASGRP1, RASGRP3, RASSF1, RASSF3, RASSF7, RASSF8, RB1, RB1CC1, RBBP4, RBBP6, RBBP8, RBM3, RBM47, RBM5, RBP1, RBP2, RBX1, RCAN3, RD3, REG4, RELA, REPS2, RERG, RET, REV3L, RFC1, RFX6, RFXAP, RGMB, RGS1, RGS16, RGS17, RGS2, RGS22, RGS6, RGSL1, RHBDD2, RHO, RHOB, RHOBTB2, RHOC, RHOD, RHOG, RHOJ, RHOT1, RHOU, RIN1, RIOK3, RIPK1, RIPK2, RIPK3, RLF, RNASEL, RND3, RNF111, RNF13, RNF180, RNF2, RNF4, RNF40, RNF43, RNH1, ROBO1, ROBO3, ROBO4, ROCK1, ROCK2, ROR1, ROR2, RORA, RP1, RPA1, RPE, RPL15, RPL26, RPL39, RPL41, RPL7, RPN2, RPS12, RPS3, RPS6KB1, RPSA, RRBP1, RRM1, RRM2, RRP1B, RSPO2, RTKN, RUFY3, RUNX1, RUNX1T1, RUNX2, RUNX3, RXFP1, RXRA, RYBP, S100A11, S100A2, S100A6, S100A7, S100A8, S100A9, S100B, S100P, S100PBP, S100Z, S1PR3, SAA2, SACS, SALL4, SAMD9, SARS, SART1, SART3, SASH1, SATB2, SCAI, SCAMP1, SCARA5, SCGB2A2, SCN7A, SCRIB, SCUBE2, SCUBE3, SDC1, SDC2, SDC4, SDCBP, SDHA, SDHC, SDPR, SEC14L2, SEC23A, SEC62, SEL1L, SELP, SEMA3E, SEMA3F, SEMA4C, SEMA6D, SENP1, SENP2, SENP3, SERPINA1, SERPINA3, SERPINA5, SERPINB13, SERPINB2, SERPINB3, SERPINB5, SETD2, SETDB1, SF3B1, SFPQ, SFRP1, SFRP2, SFRP4, SGPP1, SGPP2, SGTA, SH2B1, SH3BGRL, SH3GL2, SH3GLB2, SH3PXD2B, SHB, SHE, SHH, SHISA3, SHMT1, SHOC2, SHOX2, SI, SIAH2, SIN3A, SIPA1, SIRT1, SIRT2, SIRT3, SIX2, SIX3, SIX4, SKA3, SKAP2, SKI, SKP1, SKP2, SLC19A1, SLC19A3, SLC22A17, SLC22A18, SLC25A1, SLC28A3, SLC29A1, SLC29A3, SLC2A1, SLC38A1, SLC39A14, SLC5A8, SLC6A14, SLC7A11, SLC7A5, SLCO1B1, SLCO1B3, SLIT3, SLITRK3, SLITRK6, SLK, SLN, SMAD1, SMAD2, SMAD3, SMAD4, SMAD5, SMAD7, SMAP1, SMARCA4, SMARCA5, SMARCB1, SMARCC1, SMARCD1, SMC4, SMO, SMR3A, SMS, SMURF1, SMURF2, SMYD2, SMYD3, SNAI2, SNAI3, SNAPIN, SND1, SNTB2, SNX6, SNX9, SOCS1, SOCS2, SOCS3, SOD2, SOD3, SOHLH2, SOS1, SOST, SOX10, SOX11, SOX12, SOX17, SOX2, SOX3, SOX4, SOX6, SOX7, SOX8, SOX9, SP1, SP100, SP3, SP6, SPAG5, SPAG9, SPARC, SPARCL1, SPDEF, SPIN1, SPINT2, SPOCK1, SPOP, SPR, SPRED1, SPRR2A, SPRR3, SPRY1, SPRY2, SPRY4, SPTAN1, SQLE, SQSTM1, SRC, SRD5A1, SRD5A2, SRF, SRPK1, SRRM4, SSBP1, SSRP1, SST, SSTR2, SSTR3, SSTR5, SSX1, SSX2IP, ST13, SLC9A9, ST3GAL6, ST6GALNAC2, STAG2, STARD10, STARD13, STAT1, STAT3, STAT4, STAT5B, STAT6, STC2, STEAP1, STEAP2, STIM2, STIP1, STK33, STK39, STK4, STMN1, STRAP, STRN, STS, STX6, STYK1, SUDS3, SUFU, SULF1, SULF2, SULT1E1, SUMO1, SUMO3, SUSD2, SUZ12, SVEP1, SYK, TAC1, TACC2, TACC3, TACSTD2, TAGLN, TAGLN2, TANK, TARBP2, TAT, TBC1D16, TBK1, TBP, TBX2, TBX21, TBX3, TBX4, TBX5, TBXAS1, TCEB1, TCF12, TCF21, TCF3, TCF4, TCF7, TCF7L2, TDGF1, TDO2, TDP1, TDRD1, TEAD4, TEC, TEF, TEK, TERT, TES, TET1, TET2, TEX101, TF, TFAP2A, TFAP2C, TFAP2E, TFCP2, TFEB, TFF1, TFF2, TFF3, TFG, TFPI, TFPI2, TG, TGFA, TGFB1, TGFBI, TGFBR2, TGFBR3, TGIF1, TGM2, TGM3, THBS1, THBS4, THOC1, THRSP, THY1, TIAF1, TIAM2, TIMELESS, TIMM17A, TIMP2, TIMP3, TIMP4, TJP1, TKTL1, TLE1, TLE4, TLN1, TLR3, TLR4, TLR5, TLR7, TLR8, TLR9, TM4SF1, TM4SF5, TM9SF4, TMED3, TMEM100, TMEM127, TMEM14A, TMEM174, TMEM207, TMEM25, TMEM33, TMEM45B, TMEM97, TMOD1, TMPRSS2, TMPRSS3, TMPRSS4, TNFAIP1, TNFRSF10A, TNFRSF10B, TNFRSF1B, TNK2, TNS1, TNS3, TNS4, TOB1, TOB2, TOM1, TOM1L1, TOMM34, TOP1, TOPBP1, TOX, TP53, TP53BP2, TP53INP1, TP63, TP73, TPD52, TPM3, TPO, TPR, TRAF2, TRAF4, TRAF6, TREM2, TRH, TRIB1, TRIB2, TRIB3, TRIM16, TRIM31, TRIM33, TRIM37, TRIM44, TRIM59, TRIM66, TRIM9, TRIT1, TRPA1, TRPC1, TRPC6, TRPM2, TRPM7, TRPM8, TRPV1, TRPV5, TRPV6, TSC1, TSC2, TSG101, TSLP, TSPAN1, TSPAN12, TSPAN7, TSPAN8, TSPAN9, TSPYL5, TSSC1, TTC4, TTF1, TTK, TTYH2, TUSC1, TWIST1, TXN, TFE3, TRPS1, TUBB3, TUSC3, TYK2, TYMS, TYR, TYRO3, TYRP1, U2AF2, UBE2C, UBE2D3, UBE2Q1, UBIAD1, UCHL1, UCN, UGT2B17, ULBP2, UNC5B, UPF1, USF1, USP10, USP14, USP15, USP18, USP22, USP28, USP37, USP4, USP9X, UVRAG, VANGL2, VAPB, VASP, VAV2, VAV3, VCAM1, VCP, VDAC1, VDR, VEGFC, VEZT, VGLL2, VHL, VIM, VIP, VPS25, VRK1, VTCN1, VTI1A, VWF, WASF2, WBSCR22, WDR26, WEE1, WIF1, WIPI1, WIPI2, WISP1, WISP2, WISP3, WNT10A, WNT10B, WNT11, WNT2, WNT3, WNT3A, WNT4, WNT5B, WNT6, WNT7A, WRN, WT1, WTAP, WWP1, WWP2, WWTR1, XAF1, XBP1, XCR1, XG, XPA, XPO1, XPO5, XPO6, YBX1, YTHDC2, YWHAG, YWHAH, YWHAZ, YY1, ZAP70, ZBED3, ZBTB16, ZBTB20, ZBTB7A, ZBTB8A, ZEB2, ZFX, ZIC1, ZKSCAN3, ZMAT1, ZNF165, ZNF217, ZNF281, ZNF300, ZNF304, ZNF331, ZNF395, ZNF419, ZNF444, ZNF488, WWOX

TABLE 8B Genes in gene set for metastasis function ABCB1, ABCB5, ABCC3, ABCE1, ABCG2, ABL2, ABR, ACE2, ADAM10, ADAM19, ADAM8, ADAM9, ADAMTS1, ADAMTS5, ADIPOR1, ADIPOR2, ADM, ADO, ADORA2B, ADRB2, AFAP1, AFAP1L1, AFP, AGR2, AHNAK, AIM1, AKAP12, AKAP13, AKR1C3, AKT2, AKT3, ALDH1A1, ALDH1A3, ALK, AMOTL2, ANG, ANGPTL2, AKT1ANO1, ANO9, ANXA1, ANXA11, ANXA7, APC, APLP2, AQP3, AQP5, AQP9, ARF6, ARID1A, ARID2, ARID3B, ARID4A, ARRDC3, ATAD2, ATF3, AIF4, ATG4A, ATG5, ATM, ATOH1, ATOH8, ATP6AP2, ATP6V1C1, ATR, AURKA, AXIN2, B3GNT7, B4GALNT2, BACE1, BAD, BAG3, BAMBI, BATF2, BAX, BCAR1, BCAS3, BCAT1, BCL2, BCL2L2, BCL3, BCL6, BCL9, BDNFBIK, BIN1, BIRC5, BIRC6, BMP4, BMP7, BOLL, BPTF, BRCA1, BRCA2, BRD4, BRD8, BRMS1, BTBD7, BTG1, BTG2, BTG3, BTK, BVES, C3, C5, C6, C8orf4, C9, CA2, CA9, CACNA2D3, CACBP, CADM1, CALU, CAMP, CASP6, CBL, CBX7, CBX8, CCDC34, CCL17, CCL18, CCL19, CCL2, CCL20, CCL21, CCL22, CCL5, CCL7, CCNE1, CCNG2, CCR1, CCR4, CCR6, CCR7, CCR9, CD164, CD36, CD38, CD4, CD40, CD47, CD55, CD63, CD70, CD74, CD81, CD82, CD86, CD9, CD99, CDA, CDC20, CDC25A, CDC25B, CDC25C, CDC37, C42, CDCP1, CDH1, CDH17, CDH22, CDK4, CDK5, CDK5RAP3, CDK6, CDK8, CDKN1A, CDKN2A, CDX2, CEACAM1, CEACAM5, CFL1, CHD1L, CHEK1, CHI3L1, CHST11, CIAPIN1, CLCA1, CLCA2, CLDN10, CLOCK, CLU, CMTM3, CNTN1, COIL, COMMD1, CP, CPE, CPT1A, CRCT1, CRHR2, CRK, CRKL, CRP, CS, CSE1L, CSF1, CSK, CSPG4, CST6, CTBP1, CTBP2, CTGF, CTHRC1, CTLA4, CTTN, CUL4A, CUX1, CX3CR1, CXCL1, CXCL10, CXCL12, CXCL13, CXCL14, CXCL17, CXCL3, CXCL5, CXCL6, CXCL9, CXCR4, CXCR5, CXCR6, CYB5D2, CYLD, CYP1B1, CYP2E1, CYP2J2, CYP3A4, CYR61, DAB2IP, DACT2, DAND5, DAP, DCC, DCLK1, DDR2, DDX11, DDX20, DEK, DES, DHRS7, DKK1, DKK2, DLL4, DNM3, DNMT1, DNMT3A, DOCK1, DOT1L, DPH3, DPP4, DUSP1, DUSP6, DYRK1B, DYRK2, E2F1, E2F3, ECD, ECM1, ECT2, EDIL3, EEF1A2, EFEMP1, EGF, EGFL7, EGFR, EGR1, EIF3I, EIF4E, EIF5A2, EIF6, EMILIN1, EMP2, ENAH, ENG, ENO1, EPB41L3, EPCAM, EPHA2, EPHB2, EPHB4, EPHB6, ERBB3, ERBB4, ERCC1, ERCC2, ERCC3, ERG, ERGIC1, ESR1, ETS1, ETV1, EXT1, EYA2, EZH2, F11, F6, F8, FABP7, FADD, FANCA, FANCC, FANCD2, FAP, FAS, FASTKD2, FAT4, FBXL5, FBXO11, FBXW7, FGF10, FGF18, FGF2, FGFR1, FGFR2, FGFR3, FGFR4, FH, FHIT, FHL1, FHL2, FJX1, FLI1, FLNA, FLOT2, FLT1, FN1, FOSB, FOXA1, FOXA2, FOXC1, FOXC2, FOXD3, FOXL1, FOXM1, FOXO1, FOXO3, FOXO4, FOXP1, FOXP2, FOXP3, FOXO1, FRAT1, FSCN1, FSHR, FURIN, FUS, FUT3, FUT4, FYN, FZD5, FZD8, GAB1, GAB2, GADD45A, GAL, GALNT14, GALNT2, GAS6, GATA6, GC, GDNF, GEMIN5, GJA3, GKN1, GLB1, GLI1, GLI2, GLIPR1, GLO1, GNA13, GNAQ, GOLPH3, GPC5, GPI, GPNMB, GPR171, GPR3P, GPR55, GPR87, GPX3, GRB14, GRB2, GRK6, GRM1, HABP2, HAS2, HBD, HBP1, HDAC1, HDAC2, HDAC4, HDAC6, HES1, HES5, HEXA, HIF1A, HIPK2, HJURP, HMGA1, HMGA2, HMGB3, HMMR, HNRNPA2B1, HOOK1, HOXA1, HOXA5, HOXA9, HOXB2, HOXB9, HPR, HRG, HS3ST2, HSPA14, HTATIP2, HTRA1, HYOU1, ICMT, ID1, ID2, ID3, IDH2, IFIT2, IGF1R, IGF2, IGF2BP1, IGFBP1, IGFBP3, IGFBP5, IGFBP7, IL13, ILK, IMP3, IMPACT, ING1, ING2, ING3, ING5, IQGAP1, IRAK1, IRX2, ITGA2, ITGA3, ITGA5, ITGAV, ITGB1, ITGB3, JAG1, JAG2, JAK1, JAK2, JAK3, JMJD6, JUN, KCNJ1, KCNMA1, KDM2A, KDM4B, KDM5B, KDR, KEAP1, KIF11, KIF14, KIF15, KIF2A, KIF3C, KISS1, KIT, KITLG, KL, KLF17, XLF2, KLF4, XLF5, KLF6, KPNA2, KRAS, KRT19, KRT7, LAMB3, LAMC2, LAMP1, LAMP3, LAP3, LAPTM4B, LASP1, LATS1, LATS2, LIF, LIMK2, LIN28B, LMX1B, LOX, LOXL2, LRP1, LRP1B, LRP5, LRPPRC, LRRC4, LSM1, LYN, LZTS1, MACROD2, MADD, MAP2K4, MAP3K2, MAP3K9, MAP4K4, MAPK1, MAPKAPK2, MARCKS, MAX, MB, MBD2, MBP, MCM2, MDM4, MED1, MED12, MED27, MEF2C, MEIS1, MET, MFAP3L, MGAT1, MGMT, MIA, MIB1, MIF, MIP, MITF, MKL1, MLF2, MME, MMP10, MMP12, MMP13, MMP14, MMP28, MMP7, MMP9, MSC, MT3, MTA1, MTA2, MTA3, MTBP, MTDH, MTMR3, MTOR, MTSS1, MTUS1, MUC16, MUC4, MUSK, MVD, MVP, MX1, MYC, MYCN, MYD88, MYH9, MYD5B, NAP1L1, NAV1, NCK2, NCOA1, NDC80, NDRG2, NEDD1, NEDD4, NEDD4L, NET1, NF1, NFAT5, NGF, NHS, NKD1, NKD2, NLK, NLRP3, NME1, NOB1, NODAL, NOG, NOTCH1, NOTCH3, NOV, NOX1, NOX4, NPM1, NPS, NTSR1, NUAK1, NUMB, NUP88, OLA1, ORAI1, OSM, OTUB1, P4HA1, PAK2, PAK4, PALB2, PARP1, PAX3, PAX7, RAX8, PBK, PC, PCBP1, PCNA, PDC, PDCD4, PDCD5. PDGFRA, PDK3, PDPN, PEG10. PELP1,, PER2, PFKFB3, PGC, PHF8, PHLDA1, PIAS1, PICK1, PIGS, PIK3CA, PIKFYVE, PIN1, PIP4K2B, PIR, PIWIL1, PIWIL2, PKN1, PLA2G16, PLAUR, PLD2, PLK1, PMAIP1, PMEPA1, PMP22, POLB, PPARG, PPP1CA, PRAME, PRC1, PRDM14, PREX2, PRKCZ, PRXD1, PRL, PRMT1, PRMT5, PROK1, PROX1, PRSS3, PRUNE, PSCA, PTEN, PTER, PTG82, PTH, PTK6, PTK7, PTP4A3, PTPN13, PVR, QKI, RAB17, RAB22A, RAB25, RAB27B, RAB3D, RAB40B, RAB40C, RABL3, RAC1, RAC2, RACGAP1, RALA, RALB, RAMP3, RAN, RAP1A, RAP1B, RAP1GAP, RAP2B, RASAL2, RASSF3, RB1, RBP2, RBX1, RCAN3, RET, RGMB, RGS16, RHBDD2, RHO, RHOB, RHOBTB2, RHOC, RHOJ, RIN1, RIPK1, RIPK3, RNF111, RNF43, ROBO1, ROBO3, ROCK1, ROCK2, ROR1, ROR2, RPA1, RPL39, RPS12, RPS3, RPS6KB1, RREB1, RRM1, RRM2, RRP1B, RSPO2, RUNX2, RUNX3, RXFP1, S100A11, S100A2, S100A6, S100A7, S100A8, S100A9, S100B, S100P, S1PR3, SALL4, SART1, SASH1, SATB2, SCAI, SCAMP1, SCRIB, SDC1, SERPINB2, SETDB1, SFRP1, SFRP2, SH3GL2, SHH, SHMT1, SI, SIAH2, SIRT1, SIRT2, SKI, SKP2, SLC9A3, SLC38A1, SMAD1, SMAD2, SMAD3, SMAD4, SMAD7, SMO, SMYD3, SNAI2, SND1, SNTB2, SOCS3, SOD2, SOD3, SOX10, SOX12, SOX17, SOX2, SOX4, SOX6, SOX7, SOX9, SP1, SP3, SPAG5, SPAG9, SPARC, SPARCL1, SPDEF, SPOCK1, SPOP, SPRY1, SPRY4, SPTAN1, SQLE, SQSTM1, SRC, SRD5A2, SRF, SRPK1, SRRM4, SSTR2, SSX2IP, STARD13, STAT1, STAT3, STAT5B, STIP1, STMN1, STS, SULF1, SULF2, SUZ12, SYK, TACC3, TAGLN, TAT, TBK1,TBX2, TCEB1, TCF4, TCF7, TCF7L2, TDGF1, TEAD4, TERT, TET1, TF, TFF1, TFF3, TFPI, TG, TGFB1, TGFBI, TGIF1, TGM2, THY1, TIMM17A, TIMP2, TKTL1, TLR3; TLR4, TLR9, TM4SF1, TMED3, TMPRSS2, TMPRSS4, TNFAIP1, TNK2, TOB1, TOP1, TOPBP1, TP53, TRAF2, TRAF4, TRAF6, TRIB3, TRIM59, TRPA1, TRPM7, TRPM8, TRPV6, TSC2, TSG101, TSPAN12, TSPAN8, TSPAN9. TTYH2, TWIST1, TXN, TYR, UBE2Q1, UCHL1, UCN, UNC5B, USP10, USP15, USP18, USP22, USP37, USP9X, UVRAG, VASP, VAV2, VAV3, VCP, VEGFC, VEZT, VHL, VIP, VRK1, VTCN1, WBSCR22, WDR26, WEE1, WISP1, WNT10A, WNT10B, WNT3A, WNT5B, WT1, WTAP, WWP1, XAF1, XCR1, χPO1, YWHAZ, YY1, ZBED3, ZBTB7A, ZEB2, ZFX, ZKSCAN3, ZNF217, ZNF300, ZNF304, ZNF488, ALCAM, AR, ASAP1, DACH1, DLC1, PIEZO1, MMP16, PAG1, TUPS1, TUSC3, WWOX

TABLE 8C Genes in gene set for biomarker analysis ABAT, ABCA13, ABCB1, ABCC2, ABCG2, ACE2, ACP1, ACTN4 ADAM10, ADAM8, ADAM9, ADAMTS1, ADAMTS5, ADO, AFAP1, AFP, AGBL2, AGR2, AIM1, AKR1B10, AKT1, AKT2, ALDH1A1, ALDH1A3, ALK, ALCAM, ANG, ANLN, ANXA1, ANXA2, APC, APOA1, APOBEC3G, AQP1, AQP3, AQP5, AR, ARG1, ARHGEF7, ARID1A, ARPC1B, ASAP1, ASCL2, ASPM, ATAD2, ATF3, ATF5, ATM, ATOH8, BAD, BAMBI, BARX2, BATF2, BAX, BCL10, BCL2, BCL2L12, BCL6, BCOR, BCORL1, BDNF, BID, BIRC5, BMP4, BMP7, BMPR1A, BRCA1, BRCA2, BRE, BRMS1, BTBD7, BTC, BTG1, BTG3, BVES, C10orf10, C3, C6orf106, CA9, CACBP, CAD, CADM1, CAMP, CASK, CASP8, CASR, CBX7, CCL17, CCL19, CCL2, CCL20, CCL21, CCL4, CCL5, CCL7, CCNB1, CCNE1, CCNG2, CCNY, CCR6,, CCR7, CCT2, CD109, CD14, CD163, CD1A, CD4, CD40, CD47, CD55, CD74, CD82, CD9, CDC20, CDC25B, CDC25C, CDC42, CDC6, CDCP1, CDH1, CDH13, CDK4, CDK5, CDK8, CDKN2A, CDX2, CEACAM1, CES2, CFL1, CHD1L, CHEK1, CHEK2, CHRM3, CHRNA3, CIAPIN1, CISH, CLDN16, CLIC4, CLOCK, CLPTM1L, COIL, COL1A1, COL1A2, COMT, CP, CPE, CRK, CRKL, CRNN, CRP, CRTC1, CRTC3, CSE1L, CSNK1A1, CSPG4, CTBP2, CTGF, CTHRC1, CTNNB1, CTTN, CX3CL1, CX3CR1, CXCL1, CXCL10, CXCL12, CXCL14, CXCL5, CXCL9, CXCR4, CXCR6, CYB5A, CYP17A1, CYP19A1, CYP1A1, CYP24A1, CYP2B6, CYP3A4, CYP3A5, CYR61, DAB2, DACH1, DACH2, DACT2, DAND5, DAP, DCC, DCX, DDC, DDX1, DEC1, DEX, DES, DICER1, DIXDC1, DLC1, DLG5, DLK1, DLL4, DLX2, DLX5, DPP4, E2F1, EBP, ECD, ECM1, ECT2, EDIL3, EEF1A2, EFEMP1, EGF, EGR3, EGFL7, EGFR, EIF3E, EIF3I, EIF4E, EIF5A2, ENO1, EPAS1, EPCAM, EPHA2, EPHA3, EPHA7, EPHB4, EPHB6, EPO, EPS15, EPS8, ERBB3, ERBB4, ERCC1, ERG, ERP29, ESR1, ESR2, EVA2, EZH2, F2, FABP1, FABP4, FADD, FAM3C, FANCF, FAP, FAS, FBXO11, FBXW7, FER, FGF14, FGF2, FGFBP1, FGFR1, FGFR2, FGFR3, FGFR4, FHIT, FHL1, FHL2, FKBPL, FLNA, FLT1, FLT3, FLT4, FN1, FOXA1, FOXC1, FOXC2, FOXD3, FOXF2, FOXL1, FOXM1, FOXO3, FOXO4, FOXP1, FOXP3, FOXQ1, FRAT1, FSCN1, FURIN, FZD1, GAB2, GAL, GALNT9, GAS6, GATA2, GATA5, GATA6, GBP2, GC, GCG, GDF15, GGH, GIP, GIPC1, GLA, GLI1, GNAQ, GOLPH3, GPRC5A, GPX3, GRB2, GRM4, GSTP1, GTSE1, HAPLN3, HDAC1, HDAC2, HDAC6, HDGF, HES1, HIF1A, HK1, HMGA1, HMGA2, HMGB3, HNF1A, HOMER1, HOXA13, HOXA9, HOXB9, HPSE, HR, HSD3B1, HSPA2, HTATIP2, HTR42, HTRA3, HUWE1, HYOU1, ID2, ID3, IGF1R, IGFBP7, IL10, IL13, ILK, IMP3, IMPACT, ING3, IQGAP1, IQGAP2, IRX5, ITGA3, ITGA8, ITGB1, ITGB3, ITGB4, ITGBL1, JAK2, JMJD6, JUN, KCNJ1, KDM3A, KDM5C, KDR, KEAP1, KIAA0101, KIF14, KIF18A, KIF26B, KIF2A, KISS1, KIT, KLF17, KLF4, KLF6, KLK10, KLK3, KPNA2, KRAS, KRT7, LAMP3, LAPTM4B, LAT, LEP, LETM1, LIFR, LIG4, LIN28B, LMO7, LOX, LOXL2, LRG1, LYN, LZTS1, MAGEC2, MAGI1, MAML2, MAP4K3, MAP4K4, MARCKS, MAX, MB, MBP, MCM2, MET, MGMT, MGST1, MIA, MIB1, MIF, MIP, MITF, MMP11, MMP13, MMP16, MMP14, MMP7, MMP9, MMPO, MSX2, MTA1, MTA2, MTA3, MTBP, MTDH, MTHFD2, MTOR, MTSS1, MTUS1, MUC16, MUC2, MUC4, MVD, MVP, MYC, MYCN, MYD88, MYH9, MZF1, NAT1, NCK1, NCK2, NCOA2, NCDA5, NCOR1, NCOR2, NCSTN, NDRG2, NDRG3, NDRG4, NEDD4L, NEK2, NETO2, NEU3, NKD1, NKTR, NLK, NME1, NOB1, NOD2, NODAL, NOTCH1, NOTCH3, NOTCH4, NOV, NPM1, NQD2, NR2F2, NR4A2, NRAS, NUCB2, NUCKS1, OAT, OLA1, OLIG1, ORAI1, OTP, OTUB1, P4HA2, PAFAH1B1, PAK4, PARP1, PARVB, PAX3, PAX6, PAX8, PBK, PBRM1, PBX3, PC, PCDH10, PCDH9, PCNA, PDCD4, PDCD6, PDGFRA, PEG10, PER1, PER2, PFKPB2, PFN2PHIP, PHLDA1, PHLPP1, PHLPP2, PIGR, PIK3CA, PIK3CB, PIK3R1, PIP4K2B, PITX2, PIWIL2, PLA2G16, PLAGL1, PLAUR, PML, POLE, POMC, PPARG, PPM1D, PRAME, PRDX1, PRDX4, PRL, PROK1, PROM1, PROX1, PRSS3, PRUNE, PSCA, PTEN, PTGIS, PTGS2, PTK7, PTOV1, PTP4A3, RAB25, RAB27B, RAC1, RACGAP1, RAD50, RAD51, RALBP1, RALY, RAN, RASGRP3, RBM3, RBX1, REG4, RELA, REPS2, RET, RGS1, RGS6, RHO, RHOC, RIPK2, ROBO1, ROCK1, ROCK2, ROR1, ROR2, RRM1, RUNX2, RUNX3, S100A11, S100A2, S100A6, S100A9, S100B, S100P, SATB2, SCRIB, SCUBE2, SDC1, SDC2, SDHA, SELP, SEMA3F, SERPINB2, SETDB1, SF3B1, SFRP1, SGTA, SH2B1, SIAH2, SIPA1, SIRT1, SIX3, SIX4, SKI, SKP2, SLC19A1, SLC9A9, SLC22A18, SLC25A1, SLC29A3, SLCO1B1, SLCO1B3, SLN, SMAD1, SMAD2, SMAD3, SMAD4, SMAD7, SMYD2, SMYD3, SNAI2, SOCS3, SOD2, SOX10, SOX11, SOX17, SOX2, SOX4, SOX7, SOX8, SOX9, SP1, SPAG5, SPARC, SPARCL1, SRC, SRPK1, SST, STAG2, STARD10, STARD13, STAT1, STAT3, STAT6, STC2, STIP1, ST8, STYK1, SULT1E1, SUZ12, SYK, TACC2, TACSTD2, TAT, TBX2, TCF3, TEK, TFE3, TERT, TET1, TF, TFF3, TFPI, TGF81, TGFBI, TGM2, TGM3, THY1, TIMM17A, TKTL1, TLR4, TMPRSS2, TMPRSS3, TMPRSS4, TP53, TPD52, TRAF2, TRAF6, TRPM7, TRPS1, TSG101, TSPYL5, TUBB3, TWIST1, TYMS, UBE2C, UCN, USP10, USP14, USP22, USP9X, VAV3, VDAC1, VHL, VIP, WNT10A, WNT10B, WNT11, WNT2, WNT7A, WWOX, WWP1, XPA, XPO5, YY1, ZEB2, ZFX, ZMAT1, ZNF217

TABLE 9A ROC-AUC comparisons of panMPS and other MPS versions developed by using subsets of genes based on Z_(genes) score thresholds and clump representations. No. of No. of Distribution genes clumps MSK_Prostate Duke_Prostate Montefiore_TNBC MSK_Lung *Z_(genes) score ≥ 4 33 21 0.69 0.70 0.73 0.87 Z_(genes) score ≥ 4 43 21 0.68 0.73 0.77 0.88 *Z_(genes) score ≥ 3 68 43 0.71 0.70 0.73 0.93 Z_(genes) score ≥ 3 100 43 0.70 0.72 0.74 0.94 panMPS 295 67 0.71 0.72 0.75 0.94 *Only highest Zgenes-score gene in clump

TABLE 9B Linear regression model (r²) between panMPS and other MPS versions developed by using subsets of genes based on Z_(genes) score thresholds and clump representations. No. of No. of Distribution genes clumps MSK_Prostate Duke_Prostate Montefiore_TNBC MSK_Lung *Z_(genes) score ≥ 4 33 21 0.89 0.87 0.83 0.83 Z_(genes) score ≥ 4 43 21 0.93 0.92 0.84 0.86 *Z_(genes) score ≥ 3 68 43 0.94 0.94 0.93 0.94 Z_(genes) score ≥ 3 100 43 0.97 0.97 0.94 0.96 panMPS 295 67 1 1 1 1 *Only highest Z_(genes) score gene in clump

TABLE 10A Clinical and histological characteristics of samples used to validate the panMPS model for metastatic outcome for prostate cancer Cohort MSK Prostate CA Duke Prostate CA mPT iPT mPT iPT P Outcome n 25 260 37 39 Age Mean 58.93 58.15 64.19 61.82 0.5  Median 59.47 58.13 64 62 Standard deviation 7.23 6.82 6.48 8.41 Range 46-71 37-75 47-77 46-77 Clinical stage T1C 10 (3.51%) 146 (51.22%) 18 (23.68%) 24 (31.57%) 7.56 × 18⁻⁸ T2 11 (3.86%) 106 (37.19%) 9 (11.84%) 4 (5.26%) 3.86 × 10⁻⁵ T3 4 (1.40%) 8 (2.81%) 0 (0%) 0 (0%) Path stage T2 7 (2.46%) 156 (54.74%) 6 (7.89%) 9 (11.84%) 1.53 × 10⁻⁴ T3 13 (4.56%) 92 (32.28%) 24 (31.57%) 26 (34.21%) 3.85 × 10⁻⁶ T4 5 (1.75%) 12 (4.21%) 7 (9.21%) 4 (5.26%) 0.12 Biopsy Gleason score 3 0 (0%) 0 (0%) 0 (0%) 1 (1.31%) 4 0 (0%) 0 (0%) 1 (1.31%) 0 (0%) 5 0 (0%) 2 (0.70%) 0 (0%) 4 (5.26%) 6 7 (2.46%) 142 (49.82%) 10 (13.51%) 18 (23.68%) 1.91 × 10⁻⁵ 7 12 (4.21%) 92 (32.28%) 14 (18.42%) 12 (15.78%) 1.19 × 10⁻⁵ 8 5 (1.75%) 15 (5.26%) 5 (6.57%) 0 (0%) 0.01 9 0 (0%) 9 (3.16%) 3 (3.94%) 4 (5.26%) 0.06 10 0 (0%) 0 (0%) 1 (1.31%) 0 (0%) Path Gleason score 6 1 (0.35%) 68 (23.86%) 2 (2.63%) 2 (2.63%) 0.01 7 8 (2.81%) 173 (60.70%) 20 (26.31%) 29 (38.16%)  9.27 × 10⁻¹⁰ 8 6 (2.11%) 10 (3.51%) 2 (2.63%) 3 (3.95%) 9 19 (6.66%) 8 (2.81%) 12 (15.785) 5 (6.58%) 10 0 (0%) 0 (0%) 1 (1.31%) 0 (0%) Preop PSA (ng/mL) Median 8.49 5.6 7.5 7.3 <4 4 (1.40%) 46 (16.14%) 4 (5.26%) 4 (5.26%) 4-10 10 (3.51%) 163 (57.19%) 16 (21.05%) 27 (35.52%) >10 11 (3.86%) 50 (17.54%) 17 (22.36%) 8 (10.52%) P-values were determined by Wilcoxon Rank Sum Test and Fisher's Exact Test respectively for continuous and categorical variables for inter cohort significance.

TABLE 10B Clinical and histological characteristics of samples used to validate the panMPS model for metastasis outcome for TNBC Cohort Montefiore TNBC mBC iBC Outcome n 28 13 Age Mean 58.3 53 Median 61.5 49 Standard deviation 11.57 11.7 Range 35-82 34-74 TNM Stage T1 4 (9.75%) 5 (12.19%) T2 7 (17.07%) 5 (12.19%) T3 4 (9.75%) 0 (0%) T4 2 (4.88%) 0 (0%)

TABLE 10C Clinical and histological characteristics of samples used to validate the panMPS model for metastasis outcome for TNBC Cohort MSK Lung Adeno CA mLA iLA Outcome n 23 10 Sex Male 11 (26.83%) 4 (9.76%) Female 12 (29.27%) 6 (14.63%) TNM Stage 1B 6 (14.63%) 0 (0%) 2 7 (17.07%) 1 (2.44%) 3 10 (24.39%) 5 (12.20%) 4 2 (4.88%) 4 (9.76%)

TABLE 11 AUC of Distribution of MPS genes based on lowest Z_(genes) scores in clumps No. of No. of Distribution genes clumps MSK_Prostate Duke_Prostate Montefiore_TNBC MSK_Lung 33 21 0.67 0.67 0.78 0.87 Z_(genes) score ≥ 4 43 21 0.68 0.73 0.77 0.88 68 43 0.69 0.69 0.75 0.93 Z_(genes) score ≥ 3 100 43 0.7 0.72 0.74 0.94 *panMPS 175 67 0.7 0.72 0.76 0.97 panMPS 295 67 0.71 0.72 0.75 0.94 *Only lowest Zgenes-score gene in clump

TABLE 12 r² of Distribution of MPS genes based on lowest Zgenes scores in clumps No. of No. of Distribution genes clumps MSK_Prostate Duke_Prostate Montefiore_TNBC MSK_Lung 33 21 0.75 0.57 0.67 0.59 Z_(genes) score ≥ 4 43 21 0.93 0.92 0.84 0.86 68 43 0.81 0.64 0.73 0.71 Z_(genes) score ≥ 3 100 43 0.97 0.97 0.94 0.96 *panMPS 175 67 0.89 0.75 0.84 0.84 panMPS 295 67 1 1 1 1 *Only lowest Z_(genes) score gene in clump

TABLE 13 MPS Genes index gene NYU_Z NYU_dir MSKs1_Z MSKs1_dir MSKs2_Z MSKs2_dir 1 CLCNKB NA NA NA NA 2.0 1 2 ARHGEF10L NA NA 2.1 −1 NA NA 3 ACTL8 NA NA 1.9 −1 NA NA 4 DPYD NA NA NA NA 2.9 −1  5 COL11A1 NA NA NA NA 1.9 −1  6 NRXN1 NA NA NA NA 3.2 −1  7 CTNNA2 NA NA NA NA 1.8 −1  8 ALCAM NA NA NA NA 2.5 1 9 ZBTB20 NA NA 1.8  1 NA NA 10 MYLK NA NA 2.8  1 NA NA 11 KALRN NA NA 2.4  1 NA NA 12 BFSP2 NA NA 2.4  1 NA NA 13 SLC9A9 NA NA 2.7  1 NA NA 14 KCNAB1 NA NA 5.8  1 NA NA 15 PPM1L NA NA 2    1 NA NA 16 MECOM NA NA 2    1 NA NA 17 DGKG NA NA 1.9  1 NA NA 18 TP63 NA NA 3    1 NA NA 19 LEPREL1 NA NA 2.6  1 NA NA 20 BOD1L NA NA NA NA 2.4 −1  21 KCTD8 NA NA NA NA 2.8 −1  22 GABRA2 NA NA NA NA 2.3 −1  23 LPHN3 NA NA NA NA 2.5 −1  24 GRID2 NA NA NA NA 5.1 −1  25 DCHS2 NA NA NA NA 2.6 −1  26 GLRB NA NA NA NA 2.7 −1  27 GRIA2 NA NA NA NA 2.3 −1  28 FSTL5 NA NA NA NA 2.2 −1  29 CENPH NA NA 1.9 −1 NA NA 30 MRPS36 NA NA 2.6 −1 NA NA 31 CDK7 NA NA 2.7 −1 NA NA 32 CCDC125 NA NA 2   −1 NA NA 33 TAF9 NA NA 2.6 −1 NA NA 34 RAD17 NA NA 2.6 −1 NA NA 35 MARVELD2 NA NA 3   −1 NA NA 36 MEF2C NA NA NA NA 2.3 −1  37 TICAM2 NA NA NA NA 1.8 −1  38 COL21A1 NA NA NA NA 1.8 −1  39 COL19A1 NA NA NA NA 3.4 −1  40 COL12A1 NA NA NA NA 1.6 −1  41 UBE2CBP 2.8 −1 NA NA NA NA 42 ME1 2.5 −1 NA NA NA NA 43 MAP3K7 NA NA NA NA 3.2 −1  44 EPHA7 NA NA NA NA 1.8 −1  45 FBXL4 NA NA NA NA 1.7 −1  46 SIM1 NA NA NA NA 2.2 −1  47 ASCC3 NA NA NA NA 1.8 −1  48 NUS1 NA NA NA NA 2.2 −1  49 TRDN NA NA NA NA 3.0 −1  50 UTRN NA NA NA NA 2.3 −1  51 EPM2A NA NA NA NA 2.4 −1  52 GRM1 NA NA NA NA 1.9 −1  53 C6orf118 NA NA NA NA 2.8 −1  54 PDE10A NA NA NA NA 4.7 −1  55 IQCE NA NA NA NA 1.8 1 56 FBXL18 NA NA NA NA 1.9 1 57 STX1A NA NA NA NA 2.2 1 58 CLDN3 NA NA NA NA 2.6 1 59 EIF4H NA NA NA NA 2.0 1 60 LAT2 NA NA NA NA 2.0 1 61 RFC2 NA NA NA NA 1.8 1 62 CLIP2 NA NA NA NA 3.1 1 63 HIP1 NA NA NA NA 4.4 1 64 TMEM120A NA NA NA NA 1.7 1 65 STYXL1 NA NA NA NA 2.3 1 66 MDH2 NA NA NA NA 2.0 1 67 YWHAG NA NA NA NA 2.7 1 68 STAG3 NA NA NA NA 2.4 1 69 PILRB NA NA NA NA 2.9 1 70 PILRA NA NA NA NA 1.9 1 71 MEPCE NA NA NA NA 2.1 1 72 TSC22D4 NA NA NA NA 2.1 1 73 C7orf51 NA NA NA NA 2.2 1 74 AGFG2 NA NA NA NA 2.3 1 75 LRCH4 NA NA NA NA 2.2 1 76 FBXO24 NA NA NA NA 2.5 1 77 PCOLCE NA NA NA NA 1.8 1 78 MOSPD3 NA NA NA NA 2.3 1 79 TFR2 NA NA NA NA 2.6 1 80 ACTL6B NA NA NA NA 1.7 1 81 GIGYF1 NA NA NA NA 2.7 1 82 EPO NA NA NA NA 2.0 1 83 CPA2 NA NA NA NA 2.1 1 84 CPA4 NA NA NA NA 1.9 1 85 CPA5 NA NA NA NA 2.8 1 86 CPA1 NA NA NA NA 2.1 1 87 TSGA14 NA NA NA NA 9.4 1 88 MEST NA NA NA NA 3.2 1 89 COPG2 NA NA NA NA 3.1 1 90 ARHGEF5 NA NA NA NA 2.7 1 91 DLGAP2 NA NA 2.2 −1 NA NA 92 ARHGEF10 NA NA 2.9 −1 NA NA 93 MYOM2 2.1 −1 NA NA NA NA 94 CSMD1 NA NA NA NA 4.6 −1  95 MFHAS1 3.3 −1 NA NA NA NA 96 ERI1 1.9 −1 NA NA NA NA 97 TNKS 4   −1 NA NA NA NA 98 MSRA 5.1 −1 NA NA NA NA 99 C8orf16 2.2 −1 NA NA NA NA 100 MTMR9 1.9 −1 NA NA NA NA 101 BLK 2.1 −1 NA NA NA NA 102 GATA4 3.2 −1 NA NA NA NA 103 NEIL2 2.7 −1 NA NA NA NA 104 CTSB 2.8 −1 NA NA NA NA 105 C8orf79 2.9 −1 NA NA NA NA 106 DLC1 6.5 −1 NA NA NA NA 107 SGCZ 4.7 −1 NA NA 3.5 −1  108 TUSC3 3.1 −1 NA NA NA NA 109 MTMR7 3.7 −1 NA NA NA NA 110 SLC7A2 4.1 −1 NA NA NA NA 111 PDGFRL 4.8 −1 NA NA NA NA 112 MTUS1 3.6 −1 NA NA NA NA 113 PCM1 1.7 −1 NA NA NA NA 114 ASAH1 7.1 −1 NA NA NA NA 115 NAT2 3.3 −1 NA NA NA NA 116 PSD3 7.3 −1 NA NA NA NA 117 SH2D4A 2.9 −1 NA NA NA NA 118 LZTS1 2   −1 NA NA NA NA 119 XPO7 2.3 −1 NA NA NA NA 120 FAM160B2 2.5 −1 1.8 −1 NA NA 121 NUDT18 NA NA 2.3 −1 NA NA 122 HR NA NA 2.7 −1 NA NA 123 REEP4 NA NA 2.5 −1 NA NA 124 LGI3 NA NA 2   −1 NA NA 125 BMP1 NA NA 2.2 −1 NA NA 126 PHYHIP NA NA 2.2 −1 NA NA 127 POLR3D NA NA 2.7 −1 NA NA 128 SLC39A14 1.8 −1 2.2 −1 NA NA 129 PPP3CC 3.1 −1 2.6 −1 NA NA 130 SORBS3 NA NA 3   −1 NA NA 131 PDLIM2 NA NA 2.9 −1 NA NA 132 C8orf58 NA NA 3   −1 NA NA 133 KIAA1967 2.8 −1 3.1 −1 NA NA 134 BIN3 1.7 −1 2.8 −1 NA NA 135 EGR3 NA NA 2   −1 NA NA 136 RHOBTB2 NA NA 1.7 −1 NA NA 137 TNFRSF10D 1.9 −1 NA NA NA NA 138 TNFRSF10A NA NA 2.2 −1 NA NA 139 CHMP7 NA NA 2.4 −1 NA NA 140 LOXL2 NA NA 1.9 −1 NA NA 141 ENTPD4 2.7 −1 NA NA NA NA 142 erw 2.6 −1 NA NA NA NA 143 NKX2-6 2.4 −1 NA NA NA NA 144 DOCK5 5.4 −1 NA NA NA NA 145 KCTD9 2   −1 NA NA NA NA 146 CDCA2 2   −1 NA NA NA NA 147 EBF2 5.1 −1 NA NA NA NA 148 DPYSL2 3.3 −1 NA NA NA NA 149 ADRA1A 3.9 −1 NA NA NA NA 150 STMN4 3.3 −1 NA NA NA NA 151 TRIM35 2.6 −1 NA NA NA NA 152 PTK2B 7   −1 NA NA NA NA 153 CHRNA2 3.5 −1 NA NA NA NA 154 EPHX2 3.3 −1 NA NA NA NA 155 CCDC25 4.4 −1 NA NA NA NA 156 SCARA5 3.3 −1 NA NA NA NA 157 C8orf80 3.6 −1 NA NA NA NA 158 ELP3 3.4 −1 NA NA NA NA 159 HMBOX1 1.8 −1 NA NA NA NA 160 KIF13B 2.7 −1 NA NA NA NA 161 TOX 4.3 1 NA NA NA NA 162 CYP7B1 NA NA 1.7  1 NA NA 163 CPA6 3.8 1 NA NA NA NA 164 PREX2 7.5 1 NA NA NA NA 165 C8orf34 6   1 NA NA NA NA 166 SULF1 5.2 1 3.4  1 NA NA 167 SLCO5A1 4.9 1 4.2  1 NA NA 168 PRDM14 4.7 1 NA NA NA NA 169 NCOA2 3.2 1 2.4  1 NA NA 170 LACTB2 2.6 1 NA NA NA NA 171 XKR9 2.7 1 NA NA NA NA 172 EYA1 3.4 1 NA NA NA NA 173 MSC 2   1 NA NA NA NA 174 TRPA1 2.3 1 NA NA NA NA 175 KCNB2 6.8 1 NA NA NA NA 176 RPL7 2.3 1 NA NA NA NA 177 STAU2 4.6 1 NA NA NA NA 178 TCEB1 1.8 1 NA NA NA NA 179 JPH1 6   1 NA NA NA NA 180 GDAP1 2   1 NA NA NA NA 181 PI15 3   1 NA NA NA NA 182 CRISPLD1 4.9 1 NA NA NA NA 183 HNF4G 4.1 1 NA NA NA NA 184 ZFHX4 4.3 1 NA NA NA NA 185 PKIA 3.3 1 NA NA NA NA 186 STMN2 2.8 1 NA NA NA NA 187 HEY1 3   1 NA NA NA NA 188 ZNF704 NA NA 2.5  1 NA NA 189 PAG1 NA NA 2    1 NA NA 190 IMPA1 NA NA 1.9  1 NA NA 191 RALYL 2.8 1 NA NA NA NA 192 CNGB3 1.8 1 NA NA NA NA 193 CNBD1 3.8 1 3.8  1 NA NA 194 MMP16 NA NA 3.5  1 NA NA 195 SLC26A7 NA NA 2.2  1 NA NA 196 CDH17 2.8 1 NA NA NA NA 197 PTDSS1 2.5 1 NA NA NA NA 198 SDC2 3.4 1 NA NA NA NA 199 MTDH NA NA 1.9  1 NA NA 200 NIPAL2 1.9 1 NA NA NA NA 201 STK3 1.8 1 NA NA NA NA 202 VPS13B 3.9 1 NA NA NA NA 203 RGS22 2.7 1 NA NA NA NA 204 YWHAZ NA NA 2.2  1 NA NA 205 ZNF706 NA NA 2.8  1 NA NA 206 GRHL2 NA NA 2.4  1 NA NA 207 NCALD 5.5 1 2.9  1 NA NA 208 UBR5 NA NA 2.2  1 NA NA 209 ATP6V1C1 NA NA 2.4  1 NA NA 210 RIMS2 2   1 4    1 NA NA 211 DPYS 3.2 1 NA NA NA NA 212 LRP12 NA NA 2    1 NA NA 213 ZFPM2 4.2 1 6.3  1 NA NA 214 ANGPT1 2.4 1 NA NA NA NA 215 RSPO2 1.8 1 NA NA NA NA 216 CSMD3 4.9 1 4.2  1 NA NA 217 TRPS1 2.9 1 2.7  1 NA NA 218 ZHX2 NA NA 2.6  1 NA NA 219 ANXA13 2.1 1 NA NA NA NA 220 KIAA0196 2.6 1 NA NA NA NA 221 POU5F1B 2.9 1 NA NA NA NA 222 MYC 4.2 1 NA NA NA NA 223 TMEM75 3.5 1 NA NA NA NA 224 ASAP1 NA NA 3.6  1 NA NA 225 ADCY8 3.1 1 5.4  1 NA NA 226 EFR3A 3.1 1 NA NA NA NA 227 OC90 1.9 1 NA NA NA NA 228 KCNQ3 6   1 NA NA NA NA 229 TMEM71 2.9 1 NA NA NA NA 230 PHF20L1 2.8 1 NA NA NA NA 231 TG 3.8 1 NA NA NA NA 232 SLA 2.2 1 NA NA NA NA 233 WISP1 2.2 1 NA NA NA NA 234 ZFAT 2.5 1 NA NA NA NA 235 PTK2 NA NA 2.3  1 NA NA 236 GRK5 NA NA 2.4 −1 NA NA 237 RCOR2 NA NA NA NA 1.7 1 238 MACROD1 NA NA 1.9  1 2.9 1 239 STIP1 NA NA NA NA 1.8 1 240 SF1 NA NA NA NA 2.5 1 241 MEN1 NA NA NA NA 2.1 1 242 CDC42BPG NA NA NA NA 2.3 1 243 PPP2R5B NA NA NA NA 1.8 1 244 GYS2 NA NA NA NA 2.8 −1  245 PDS5B NA NA NA NA 2.0 −1  246 C13orf23 NA NA NA NA 2.2 −1  247 ENOX1 NA NA NA NA 5.6 −1  248 LRCH1 NA NA NA NA 2.4 −1  249 ESD NA NA NA NA 2.6 −1  250 HTR2A NA NA NA NA 3.3 −1  251 DIAPH3 NA NA NA NA 3.3 −1  252 PCDH9 NA NA NA NA 4.5 −1  253 KLHL1 NA NA NA NA 1.9 −1  254 DACH1 NA NA NA NA 1.9 −1  255 GPC5 NA NA NA NA 2.1 −1  256 NALCN NA NA NA NA 2.2 −1  257 TFDP1 NA NA 2.3 −1 NA NA 258 MDGA2 NA NA NA NA 2.8 −1  259 MEIS2 NA NA NA NA 3.9 −1  260 VPS13C NA NA NA NA 1.8 −1  261 TBC1D10B NA NA NA NA 1.8 1 262 RNF40 NA NA NA NA 2.1 1 263 CNGB1 1.8 −1 NA NA NA NA 264 C16orf80 2.2 −1 NA NA NA NA 265 CDH8 NA NA NA NA 3.7 −1  266 NFAT5 2.3 −1 NA NA NA NA 267 WWP2 1.8 −1 NA NA NA NA 268 DDX19A 2.3 −1 NA NA NA NA 269 ST3GAL2 2.4 −1 NA NA NA NA 270 ZFHX3 2.2 −1 NA NA NA NA 271 GLG1 2.1 −1 NA NA NA NA 272 WDR59 2.1 −1 NA NA NA NA 273 BCAR1 2.5 −1 NA NA NA NA 274 CFDP1 3   −1 NA NA NA NA 275 CNTNAP4 3.2 −1 NA NA NA NA 276 ADAMTS18 3.5 −1 NA NA NA NA 277 NUDT7 2.2 −1 NA NA NA NA 278 CLEC3A 2.3 −1 NA NA NA NA 279 WWOX 9.3 −1 NA NA NA NA 280 CDYL2 2.5 −1 NA NA NA NA 281 C16orf46 NA NA 2.2 −1 NA NA 282 GCSH NA NA 1.9 −1 NA NA 283 PKD1L2 4.9 −1 2   −1 NA NA 284 BCMO1 2.9 −1 3.6 −1 NA NA 285 GAN 2.7 −1 2.4 −1 NA NA 286 PLCG2 2.9 −1 2.7 −1 NA NA 287 HSD17B2 2.6 −1 NA NA NA NA 288 CDH13 8   −1 2.9 −1 NA NA 289 MLYCD 2.4 −1 NA NA NA NA 290 NECAB2 NA NA 2   −1 NA NA 291 MBTPS1 2.7 −1 NA NA NA NA 292 HSDL1 NA NA 2   −1 NA NA 293 LRRC50 2.4 −1 NA NA NA NA 294 WFDC1 2.3 −1 NA NA NA NA 295 ATP2C2 3.6 −1 NA NA NA NA 296 KIAA1609 NA NA 1.9 −1 NA NA 297 KLHL36 NA NA 1.8 −1 NA NA 298 USP10 2.3 −1 NA NA NA NA 299 CRISPLD2 2.5 −1 2.9 −1 NA NA 300 ZDHHC7 NA NA 2.5 −1 NA NA 301 KIAA0513 NA NA 2.1 −1 NA NA 302 KIAA0182 NA NA 2   −1 NA NA 303 GINS2 NA NA 2.1 −1 NA NA 304 C16orf74 NA NA 2.3 −1 NA NA 305 COX4NB NA NA 2.5 −1 NA NA 306 COX4I1 NA NA 2.6 −1 NA NA 307 IRF8 NA NA 2.5 −1 NA NA 308 FOXF1 NA NA 2.2 −1 NA NA 309 MTHFSD NA NA 2.4 −1 NA NA 310 JPH3 2.4 −1 2.4 −1 NA NA 311 KLHDC4 NA NA 2.5 −1 NA NA 312 SLC7A5 1.7 −1 3   −1 NA NA 313 CA5A 2.6 −1 3.8 −1 NA NA 314 BANP 2.6 −1 3.3 −1 NA NA 315 ZFPM1 NA NA 2.5 −1 NA NA 316 C16orf85 NA NA 2.1 −1 NA NA 317 ZC3H18 NA NA 2.1 −1 NA NA 318 IL17C NA NA 1.8 −1 NA NA 319 CYBA NA NA 2.9 −1 NA NA 320 MVD NA NA 2.3 −1 NA NA 321 SNAI3 NA NA 2.4 −1 NA NA 322 RNF166 NA NA 2.2 −1 NA NA 323 FAM38A NA NA 2.7 −1 NA NA 324 CDT1 NA NA 2   −1 NA NA 325 GALNS NA NA 2.3 −1 NA NA 326 TRAPPC2L NA NA 1.9 −1 NA NA 327 CBFA2T3 NA NA 1.9 −1 NA NA 328 CDH15 NA NA 1.9 −1 NA NA 329 ANKRD11 3   −1 3.7 −1 NA NA 330 FANCA NA NA 1.9 −1 NA NA 331 SPIRE2 NA NA 1.7 −1 NA NA 332 TCF25 NA NA 2.1 −1 NA NA 333 TUBB3 NA NA 2.6 −1 NA NA 334 DEF8 NA NA 1.9 −1 NA NA 335 AFG3L1 NA NA 2.3 −1 NA NA 336 GAS8 NA NA 2.9 −1 NA NA 337 DNAH2 1.8 −1 NA NA NA NA 338 NKIRAS2 NA NA NA NA 2.0 1 339 DHX58 NA NA NA NA 8.9 1 340 KAT2A NA NA NA NA 3.2 1 341 HSPB9 NA NA NA NA 2.9 1 342 RAB5C NA NA NA NA 3.5 1 343 KCNH4 NA NA NA NA 3.8 1 344 GHDC NA NA NA NA 1.8 1 345 NOTUM NA NA NA NA 2.7 1 346 ASPSCR1 NA NA NA NA 1.8 1 347 DUS1L NA NA NA NA 2.3 1 348 FASN NA NA NA NA 3.0 1 349 CDH2 NA NA NA NA 3.4 −1  350 NOL4 NA NA NA NA 3.9 −1  351 DTNA NA NA NA NA 2.2 −1  352 DCC NA NA NA NA 6.6 −1  353 WDR7 NA NA NA NA 2.0 −1  354 CD226 NA NA NA NA 3.3 −1  355 ZSWIM4 NA NA NA NA 2.8 1 356 C19orf57 NA NA NA NA 2.8 1 357 CC2D1A NA NA NA NA 4.0 1 358 RFX1 NA NA NA NA 2.2 1 359 PLCB1 NA NA NA NA 1.9 −1  360 SMARCB1 NA NA 1.8 −1 NA NA 361 TBC1D22A NA NA 4.6 −1 NA NA 362 RAB9A NA NA 3.7  1 NA NA 363 TFE3 NA NA 2.1  1 NA NA 364 HEPH 1.8 1 NA NA NA NA 365 EDA2R 2   1 NA NA NA NA 366 AR 2.3 1 2.6  1 NA NA 367 OPHN1 5.8 1 NA NA NA NA 368 NLGN4Y NA NA NA NA 2.4 −1  index gene gene_Chr gene_Cytoband gene_start gene_end 1 CLCNKB 1 p36.13 16242834 16256390 2 ARHGEF10L 1 p36.13 17738917 17896956 3 ACTL8 1 p36.13 17954395 18026145 4 DPYD 1 p21.3 97315890 98159203 5 COL11A1 1 p21.1 1.03E+08 1.03E+08 6 NRXN1 2 p16.3 49999148 51113178 7 CTNNA2 2 p12 79732191 80729415 8 ALCAM 3 q13.11 1.07E+08 9 ZBTB20 3 q13.31 1.18E+08 10 MYLK 3 q21.1 124811586 125085868 11 KALRN 3 q21.1 125296275 125922726 12 BFSP2 3 q22.1 134601480 134676746 13 SLC9A9 3 q24 144466755 145049979 14 KCNAB1 3 q25.31 157321095 157739621 15 PPM1L 3 q26.1 161956791 162271511 16 MECOM 3 q26.2 170283981 170347054 17 DGKG 3 q27.3 187347686 187562717 18 TP63 3 q28 190831910 191107935 19 LEPREL1 3 q28 191157213 191321407 20 BOD1L 4 p15.33 13179464 13238426 21 KCTD8 4 p13 43870683 44145581 22 GABRA2 4 p12 45946341 46086561 23 LPHN3 4 q13.1 62045434 62620762 24 GRID2 4 q22.1 93444831 94914730 25 DCHS2 4 q32.1 155375138 155632318 26 GLRB 4 q32.1 158216788 158312299 27 GRIA2 4 q32.1 158361186 158506677 28 FSTL5 4 q32.2 162524501 163304636 29 CENPH 5 q13.2 68521131 68541939 30 MRPS36 5 q13.2 68549329 68577710 31 CDK7 5 q13.2 68566471 68609004 32 CCDC125 5 q13.2 68612278 68664392 33 TAF9 5 q13.2 68696327 68701596 34 RAD17 5 q13.2 68700880 68746384 35 MARVELD2 5 q13.2 68746699 68773646 36 MEF2C 5 q14.3 88051922 88214780 37 TICAM2 5 q22.3 114942247 114989610 38 COL21A1 6 p12.1 56029347 56366851 39 COL19A1 6 q13 70633169 70978878 40 COL12A1 6 q14.1 75850762 75972343 41 UBE2CBP 6 q14.1 83658836 83832269 42 ME1 6 q14.2 83976827 84197498 43 MAP3K7 6 q15 91282074 91353628 44 EPHA7 6 q16.1 94007864 94185993 45 FBXL4 6 q16.2 99428055 99502570 46 SIM1 6 q16.3 100939606 101019494 47 ASCC3 6 q16.3 101062791 101435961 48 NUS1 6 q22.2 118103310 118138577 49 TRDN 6 q22.31 123579182 123999937 50 UTRN 6 q24.2 144654566 145215859 51 EPM2A 6 q24.3 145988141 146098684 52 GRM1 6 q24.3 146390611 146800427 53 C6orf118 6 q27 165613148 165643101 54 PDE10A 6 q27 165660766 165995578 55 IQCE 7 p22.2 2565158 2620893 56 FBXL18 7 p22.1 5481955 5523646 57 STX1A 7 q11.23 72751472 72771925 58 CLDN3 7 q11.23 72821263 72822536 59 EIF4H 7 q11.23 73226625 73249358 60 LAT2 7 q11.23 73261662 73282099 61 RFC2 7 q11.23 73283770 73306674 62 CLIP2 7 q11.23 73341739 73458196 63 HIP1 7 q11.23 75001345 75206215 64 TMEM120A 7 q11.23 75454238 75461913 65 STYXL1 7 q11.23 75463592 75515257 66 MDH2 7 q11.23 75515329 75533864 67 YWHAG 7 q11.23 75794053 75826252 68 STAG3 7 q22.1 99613474 99659778 69 PILRB 7 q22.1 99771673 99803388 70 PILRA 7 q22.1 99809004 99835650 71 MEPCE 7 q22.1 99865190 99869676 72 TSC22D4 7 q22.1 99902080 99914838 73 C7orf51 7 q22.1 99919486 99930358 74 AGFG2 7 q22.1 99974770 100003778 75 LRCH4 7 q22.1 100009570 100021712 76 FBXO24 7 q22.1 100021892 100036674 77 PCOLCE 7 q22.1 100037818 100043732 78 MOSPD3 7 q22.1 100047661 100050932 79 TFR2 7 q22.1 100055975 100077109 80 ACTL6B 7 q22.1 100078678 100092007 81 GIGYF1 7 q22.1 100115066 100124806 82 EPO 7 q22.1 100156359 100159257 83 CPA2 7 q32.2 129693939 129716870 84 CPA4 7 q32.2 129720230 129751249 85 CPA5 7 q32.2 129771892 129795807 86 CPA1 7 q32.2 129807468 129815165 87 TSGA14 7 q32.2 129823611 129868133 88 MEST 7 q32.2 129913282 129933363 89 COPG2 7 q32.2 129933404 129935887 90 ARHGEF5 7 q35 143683366 143708657 91 DLGAP2 8 p23.3 1436939 1644048 92 ARHGEF10 8 p23.3 1759549 1894206 93 MYOM2 8 p23.3 1980565 2080779 94 CSMD1 8 p23.2 2780282 3258996 95 MFHAS1 8 p23.1 8679409 8788541 96 ERI1 8 p23.1 8897856 8928139 97 TNKS 8 p23.1 9450855 9677266 98 MSRA 8 p23.1 9949189 10323803 99 C8orf16 8 p23.1 11021390 11025155 100 MTMR9 8 p23.1 11179410 11223062 101 BLK 8 p23.1 11388930 11459516 102 GATA4 8 p23.1 11599162 11654918 103 NEIL2 8 p23.1 11664627 11682263 104 CTSB 8 p23.1 11737442 11763055 105 C8orf79 8 p22 12847554 12931653 106 DLC1 8 p22 12985243 13416766 107 SGCZ 8 p22 13991744 15140219 108 TUSC3 8 p22 15442101 15666366 109 MTMR7 8 p22 17199923 17315207 110 SLC7A2 8 p22 17398975 17472357 111 PDGFRL 8 p22 17478443 17545655 112 MTUS1 8 p22 17545584 17702666 113 PCM1 8 p22 17824646 17935562 114 ASAH1 8 p22 17958214 17986787 115 NAT2 8 p22 18293035 18303003 116 PSD3 8 p22 18429093 18915476 117 SH2D4A 8 p21.3 19215483 19297594 118 LZTS1 8 p21.3 20147956 20205754 119 XPO7 8 p21.3 21833126 21920041 120 FAM160B2 8 p21.3 22002660 22017835 121 NUDT18 8 p21.3 22020328 22023403 122 HR 8 p21.3 22027877 22045326 123 REEP4 8 p21.3 22051478 22055393 124 LGI3 8 p21.3 22060290 22070290 125 BMP1 8 p21.3 22078645 22125782 126 PHYHIP 8 p21.3 22133162 22145796 127 POLR3D 8 p21.3 22158564 22164624 128 SLC39A14 8 p21.3 22280737 22347462 129 PPP3CC 8 p21.3 22354541 22454580 130 SORBS3 8 p21.3 22465196 22488952 131 PDLIM2 8 p21.3 22492199 22511483 132 C8orf58 8 p21.3 22513067 22517605 133 KIAA1967 8 p21.3 22518202 22533920 134 BIN3 8 p21.3 22533906 22582553 135 EGR3 8 p21.3 22601119 22606760 136 RHOBTB2 8 p21.3 22913059 22933655 137 TNFRSF10D 8 p21.3 23049051 23077485 138 TNFRSF10A 8 p21.3 23104916 23138584 139 CHMP7 8 p21.3 23157095 23175450 140 LOXL2 8 p21.3 23210097 23317667 141 ENTPD4 8 p21.3 23299386 23371081 142 erw 8 p21.2 23442308 23486008 143 NKX2-6 8 p21.2 23615909 23620056 144 DOCK5 8 p21.2 25098204 25326536 145 KCTD9 8 p21.2 25341283 25371837 146 CDCA2 8 p21.2 25372428 25421353 147 EBF2 8 p21.2 25758042 25958292 148 DPYSL2 8 p21.2 26491327 26571607 149 ADRA1A 8 p21.2 26661584 26778839 150 STMN4 8 p21.2 27149738 27171843 151 TRIM35 8 p21.2 27198321 27224751 152 PTK2B 8 p21.2 27224916 27372820 153 CHRNA2 8 p21.2 27373196 27392730 154 EPHX2 8 p21.1 27404562 27458403 155 CCDC25 8 p21.1 27646756 27686089 156 SCARA5 8 p21.1 27783672 27906117 157 C8orf80 8 p21.1 27935607 27997307 158 ELP3 8 p21.1 27999759 28104584 159 HMBOX1 8 p21.1 28803830 28966706 160 KIF13B 8 p21.1 28980715 29176529 161 TOX 8 q12.1 59880531 60194321 162 CYP7B1 8 q12.3 65671246 65873902 163 CPA6 8 q13.2 68496963 68821134 164 PREX2 8 q13.2 69026907 69306451 165 C8orf34 8 q13.2 69405511 69893810 166 SULF1 8 q13.2 70541427 70735701 167 SLCO5A1 8 q13.3 70747129 70909762 168 PRDM14 8 q13.3 71126574 71146116 169 NCOA2 8 q13.3 71178380 71478574 170 LACTB2 8 q13.3 71712045 71743946 171 XKR9 8 q13.3 71755848 71809213 172 EYA1 8 q13.3 72272222 72437021 173 MSC 8 q13.3 72916332 72919285 174 TRPA1 8 q13.3 73096040 73150373 175 KCNB2 8 q13.3 73642524 74012880 176 RPL7 8 q21.11 74365073 74375857 177 STAU2 8 q21.11 74495160 74821629 178 TCEB1 8 q21.11 75021184 75046959 179 JPH1 8 q21.11 75309493 75396117 180 GDAP1 8 q21.11 75425173 75441888 181 PI15 8 q21.11 75899327 75929819 182 CRISPLD1 8 q21.11 76059531 76109346 183 HNF4G 8 q21.11 76482732 76641600 184 ZFHX4 8 q21.11 77756078 77942076 185 PKIA 8 q21.12 79590891 79678040 186 STMN2 8 q21.13 80685916 80740868 187 HEY1 8 q21.13 80838801 80842653 188 ZNF704 8 q21.13 81713324 81949571 189 PAG1 8 q21.13 82042605 82186858 190 IMPA1 8 q21.13 82732751 82761115 191 RALYL 8 q21.2 85604112 85963979 192 CNGB3 8 q21.3 87655277 87825017 193 CNBD1 8 q21.3 87947840 88435220 194 MMP16 8 q21.3 89118580 89408833 195 SLC26A7 8 q21.3 92330692 92479554 196 CDH17 8 q22.1 95208566 95289986 197 PTDSS1 8 q22.1 97343340 97415950 198 SDC2 8 q22.1 97575058 97693213 199 MTDH 8 q22.1 98725583 98807711 200 NIPAL2 8 q22.2 99273563 99375797 201 STK3 8 q22.2 99536037 99907074 202 VPS13B 8 q22.2 100094670 100958983 203 RGS22 8 q22.2 101042452 101187520 204 YWHAZ 8 q22.3 101999980 102034745 205 ZNF706 8 q22.3 102278444 102287136 206 GRHL2 8 q22.3 102574162 102750995 207 NCALD 8 q22.3 102767947 103206311 208 UBR5 8 q22.3 103334748 103493671 209 ATP6V1C1 8 q22.3 104102424 104154461 210 RIMS2 8 q22.3 104582291 105333263 211 DPYS 8 q22.3 105460829 105548453 212 LRP12 8 q22.3 105570643 105670344 213 ZFPM2 8 q23.1 106400323 106885939 214 ANGPT1 8 q23.1 108330899 108579459 215 RSPO2 8 q23.1 108980721 109165052 216 CSMD3 8 q23.3 113304337 114518418 217 TRPS1 8 q23.3 116489900 116750429 218 ZHX2 8 q24.13 123863082 124055936 219 ANXA13 8 q24.13 124762216 124818828 220 KIAA0196 8 q24.13 126105691 126173191 221 POU5F1B 8 q24.21 128497039 128498621 222 MYC 8 q24.21 128816862 128822853 223 TMEM75 8 q24.21 129029046 129029462 224 ASAP1 8 q24.21 131133535 131483399 225 ADCY8 8 q24.22 131861736 132123854 226 EFR3A 8 q24.22 132985517 133095071 227 OC90 8 q24.22 133105667 133167084 228 KCNQ3 8 q24.22 133210438 133561961 229 TMEM71 8 q24.22 133779633 133842010 230 PHF20L1 8 q24.22 133856786 133930234 231 TG 8 q24.22 133948387 134216325 232 SLA 8 q24.22 134118155 134184479 233 WISP1 8 q24.22 134272494 134310751 234 ZFAT 8 q24.22 135559215 135794463 235 PTK2 8 q24.3 141737683 142080514 236 GRK5 10 q26.11 120957091 121205118 237 RCOR2 11 q13.1 63435303 63440892 238 MACROD1 11 q13.1 63522607 63690109 239 STIP1 11 q13.1 63709873 63728596 240 SF1 11 q13.1 64288654 64302817 241 MEN1 11 q13.1 64327564 64335342 242 CDC42BPG 11 q13.1 64348240 64368617 243 PPP2R5B 11 q13.1 64448756 64458523 244 GYS2 12 p12.1 21580390 21649048 245 PDS5B 13 q13.1 32058564 32250157 246 C13orf23 13 q13.3 38482003 38510252 247 ENOX1 13 q14.11 42685704 43259044 248 LRCH1 13 q14.13 46025304 46222786 249 ESD 13 q14.2 46243393 46269368 250 HTR2A 13 q14.2 46305514 46368176 251 DIAPH3 13 q21.2 59137718 59636120 252 PCDH9 13 q21.32 65774970 66702578 253 KLHL1 13 q21.33 69172727 69580592 254 DACH1 13 q21.33 70910099 71339331 255 GPC5 13 q31.3 90848919 92316693 256 NALCN 13 q33.1 100504131 100866814 257 TFDP1 13 q34 113287057 113343500 258 MDGA2 14 q21.3 46379045 47213703 259 MEIS2 15 q14 34970519 35189740 260 VPS13C 15 q22.2 59931884 60139939 261 TBC1D10B 16 p11.2 30275925 30288587 262 RNF40 16 p11.2 30681100 30695129 263 CNGB1 16 q13 56475004 56562513 264 C16orf80 16 q21 56705000 56720797 265 CDH8 16 q21 60244866 60628240 266 NFAT5 16 q22.1 68156498 68296054 267 WWP2 16 q22.1 68353710 68533145 268 DDX19A 16 q22.1 68938322 68964780 269 ST3GAL2 16 q22.1 68970839 69030492 270 ZFHX3 16 q22.3 71374285 71639775 271 GLG1 16 q22.3 73043357 73198518 272 WDR59 16 q23.1 73464975 73576518 273 BCAR1 16 q23.1 73820429 73859452 274 CFDP1 16 q23.1 73885109 74024888 275 CNTNAP4 16 q23.1 74868677 75150636 276 ADAMTS18 16 q23.1 75873527 76026512 277 NUDT7 16 q23.1 76313912 76333652 278 CLEC3A 16 q23.1 76613944 76623495 279 WWOX 16 q23.1 76691052 77803532 280 CDYL2 16 q23.2 79195176 79395680 281 C16orf46 16 q23.2 79644603 79668373 282 GCSH 16 q23.2 79673430 79687481 283 PKD1L2 16 q23.2 79691985 79811477 284 BCMO1 16 q23.2 79829797 79882248 285 GAN 16 q23.2 79906076 79971441 286 PLCG2 16 q23.2 80370408 80549399 287 HSD17B2 16 q23.3 80626364 80689638 288 CDH13 16 q23.3 81439761 82387705 289 MLYCD 16 q23.3 82490231 82507286 290 NECAB2 16 q23.3 82559738 82593878 291 MBTPS1 16 q24.1 82644872 82708018 292 HSDL1 16 q24.1 82713389 82736265 293 LRRC50 16 q24.1 82736366 82769024 294 WFDC1 16 q24.1 82885822 82920888 295 ATP2C2 16 q24.1 82959634 83055293 296 KIAA1609 16 q24.1 83068608 83095794 297 KLHL36 16 q24.1 83239632 83253416 298 USP10 16 q24.1 83291050 83371026 299 CRISPLD2 16 q24.1 83411113 83500614 300 ZDHHC7 16 q24.1 83565573 83602642 301 KIAA0513 16 q24.1 83618911 83685327 302 KIAA0182 16 q24.1 84202524 84267311 303 GINS2 16 q24.1 84268782 84280089 304 C16orf74 16 q24.1 84298624 84342190 305 COX4NB 16 q24.1 84369737 84390601 306 COX4I1 16 q24.1 84390697 84398109 307 IRF8 16 q24.1 84490275 84513710 308 FOXF1 16 q24.1 85101634 85105570 309 MTHFSD 16 q24.1 85121284 85157509 310 JPH3 16 q24.2 86194000 86289263 311 KLHDC4 16 q24.2 86298920 86357056 312 SLC7A5 16 q24.2 86421131 86460615 313 CA5A 16 q24.2 86479126 86527613 314 BANP 16 q24.2 86542539 86668425 315 ZFPM1 16 q24.2 87047226 87128890 316 C16orf85 16 q24.2 87147613 87164049 317 ZC3H18 16 q24.2 87164343 87225756 318 IL17C 16 q24.3 87232502 87234385 319 CYBA 16 q24.3 87237199 87244958 320 MVD 16 q24.3 87245849 87257019 321 SNAI3 16 q24.3 87271591 87280383 322 RNF166 16 q24.3 87290411 87300312 323 FAM38A 16 q24.3 87302916 87330317 324 CDT1 16 q24.3 87397687 87403166 325 GALNS 16 q24.3 87407644 87450885 326 TRAPPC2L 16 q24.3 87451007 87455020 327 CBFA2T3 16 q24.3 87468768 87570902 328 CDH15 16 q24.3 87765664 87789400 329 ANKRD11 16 q24.3 87861536 88084470 330 FANCA 16 q24.3 88331460 88410566 331 SPIRE2 16 q24.3 88422408 88465228 332 TCF25 16 q24.3 88467520 88505287 333 TUBB3 16 q24.3 88513168 88530006 334 DEF8 16 q24.3 88542684 88561968 335 AFG3L1 16 q24.3 88566489 88594696 336 GAS8 16 q24.3 88616509 88638880 337 DNAH2 17 p13.1 7562746 7677783 338 NKIRAS2 17 q21.2 37422564 37431180 339 DHX58 17 q21.2 37506979 37518277 340 KAT2A 17 q21.2 37518657 37526872 341 HSPB9 17 q21.2 37528361 37528897 342 RAB5C 17 q21.2 37530524 37560548 343 KCNH4 17 q21.2 37562439 37586822 344 GHDC 17 q21.2 37594632 37599722 345 NOTUM 17 q25.3 77503689 77512353 346 ASPSCR1 17 q25.3 77528715 77568569 347 DUS1L 17 q25.3 77609043 77629242 348 FASN 17 q25.3 77629504 77649395 349 CDH2 18 q12.1 23784934 24011189 350 NOL4 18 q12.1 29685062 30057513 351 DTNA 18 q12.1 30327279 30725806 352 DCC 18 q21.2 48121156 49311780 353 WDR7 18 q21.31 52469614 52848040 354 CD226 18 q22.2 65681175 65775140 355 ZSWIM4 19 p13.13 13767274 13804044 356 C19orf57 19 p13.12 13854168 13877909 357 CC2D1A 19 p13.12 13878014 13902691 358 RFX1 19 p13.12 13933353 13978097 359 PLCB1 20 p12.3 8061296 8813547 360 SMARCB1 22 q11.23 22459150 22506703 361 TBC1D22A 22 q13.31 45537193 45948399 362 RAB9A 23 p22.2 13617262 13637681 363 TFE3 23 p11.23 48772613 48787722 364 HEPH 23 q12 65299388 65403956 365 EDA2R 23 q12 65732204 65775608 366 AR 23 q12 66680599 66860844 367 OPHN1 23 q12 67179440 67570372 368 NLGN4Y 24 q11.221 15144026 15466924

TABLE 14 a Final- NYU- MSKa1- MSKa1- MSKa2- MSKa2- logrank- logrank- logrank- gene- gene- RANK gene index NYU-Z NYU-dir count MSKa1-Z dir count MSKa2-Z dir count n58andom n27trandom composite Cir Cytoband 1 PPP

C 129 3.1 −1 958 2.6 −1 965 NA NA NA 45 41 45 8 p21.3 2 SLCO5A1 157 4.9 1 1000 4.2 1 882 NA NA NA

13 18

q

.3 3 SLC7A5 318 1.7 −1 508 3 −1 980 NA NA NA 43 37 40 15 q24.2 4 SLC7A2 110 4.1 −1 1000 NA NA NA NA NA NA 44 43 44

p22 5 C

PLD2 299 2.8 −1 735 2.9 −1 939 NA NA NA 54 67 51 16 q24.1 6 CDH

8 −1 964 2.9 −1 767 NA NA NA 43 88 63 16 q23.3 7 CDH8 2

5 NA NA NA NA NA NA 3.7344 −1 589 15 10 11 18 q21 8 CDH2 349 NA NA NA NA NA NA 3.4456 −1

18 15 17 18 q12.1 9 ASAH1 114 7.1 −1 1000 NA NA NA NA NA NA 105 64 55 8 p2

10 KCNB2 175 6.8 1 1000 NA NA NA NA NA NA

9

4 66 8 q13.3 11 KCN

NA NA NA NA NA NA 3.7501 1 9

1 1 1 17 q21.2 12 KCTD8 21 NA NA NA NA NA NA 2.8192 −1 921 30 24 29 4 p13 13 JP

129

1 1000 NA NA NA NA NA NA 29 35 31

q21.11 14 M

T 88 NA NA NA NA NA NA 3.2032 1 940 32 32 32 7 q32.2 15 NCALC 207

.5 1 1000 2.9 1 953 NA NA NA 13 12 13 8 q22.3 16 COL18A1 38 NA NA NA NA NA NA 3.4330 −1 536

20 21.5 6 q13 17 MAP3K7 43 NA NA NA NA NA NA 3.1873 −1 929 47 54 49 6 q15 18 YWHA3 67 NA NA NA NA NA NA 2.7386 1 951 40 62 47 7 q11.23 19 NOL4 350 NA NA NA NA NA NA 3.911

−1 8

4 2 2 18 q12.1 20 ENOX1 247 NA NA NA NA NA NA 5.923

−1 1000 2 8 4 13 q14.11 21 CSMD1 94 NA NA NA NA NA NA 4.5280 −1 871

6 6 8 p25.2 22 SGCZ 107 4.7 −1 926 NA NA NA 3.

10#z,899; −1 881 9 5 7 8 p22 23 PDE10A 54 NA NA NA NA NA NA 4.8946 −1 909 8 7 8 6 q27 24 PCD

252 NA NA NA NA NA NA 4.5416 −1 962 5 19 9 13 q21.32 25 HTR2A 250 NA NA NA NA NA NA 3.2974 −1 986 10 11 10 13 q14.2 26 H

83 NA NA NA NA NA NA 4.4416 1 1000 11 14 12 7 q11.23 27 CC

354 NA NA NA NA NA NA 3.3032 −1 1000 18 9 14 18 q22.2 28 DCC 352 NA NA NA NA NA NA 6.6211 −1 1003 12 17 15 18 q21.2 29 GC2D1A 357 NA NA NA NA NA NA 3.

705 1 996 17 18 18 19 p1

.12 30 PTK28 152 7 −1 1000 NA NA NA NA NA NA 20 27 21.5 8 p21.2 31 BCMO1 284 2.9 −1 943 2.6 −1 957 NA NA NA 26 21 23 16 q23.2 32 MACRD

236 NA NA NA 1.9 1 533 2.3908 1 973 25 22 24 11 q12.1 33 GRID2 24 NA NA NA NA NA NA 5.110

−1 983 22 28 25 4 q23.1 34 DIAPH3 25

NA NA NA NA NA NA 3.2853 −1 962 36 29 27 13 q21.2 35 PILRB 68 NA NA NA NA NA NA 2.9352 1

6 35 25 28 7 q22.1 36 ME

259 NA NA NA NA NA NA 3.9425 −1 8

9 19 32 30 16 q14 37 MBRA 98 5.1 −1 999 NA NA NA NA NA NA 34 31 32 8 p23.1 38 DPYO 4 NA NA NA NA NA NA 2.8801 −1 847 38 34 34 1 p21.3 39 ANKRD11 329 3 −1 949 3.7 −1 9

NA NA NA 37 33 35 16 q24.3 40 NRXN1 6 NA NA NA NA NA NA 3.23

7 −1 840 39 38 38 2 p16.3 41 ADCY8 2

3.1 1 980 5.4 1 1000 NA NA NA 52 30 39 8 q24.22 42 TRDN 49 NA NA NA NA NA NA 3.0342 −1

38 44 41 6 q22.31 43 STAJ8 177 4.

1 1000 NA NA NA NA NA NA 45 42 43 8 q21.11 44 SP1 240 NA NA NA NA NA NA 2.4710 1 88

66 48 48 11 q18.1 45 CLIP2 62 NA NA NA NA NA NA 3.0945 1 9

57 47 50 7 q11.23 46 CLDN3 68 NA NA NA NA NA NA 2.6179 1 984 61 53 51 7 q11.23 47 ZSWIM4 357 NA NA NA NA NA NA 2.8120 1 975 60 51 57 19 p13.13 48 GLRB 26 NA NA NA NA NA NA 2.6680 −1 963 64 48 58 4 q32.1 49 CCHS2 25 NA NA NA NA NA NA 2.7

3 −1 954 68 60 64 4 q32.1 50 TRPS1 217 2.8 1 814 2.7 1 751 NA NA NA 63 65 65 8 q23.3 51 MDGA2 258 NA NA NA NA NA NA 2.8345 −1 823 69 68 68 14 q21.3 52 CNBD1 156 3.5 1 999 3.3 1 940 NA NA NA 67 70 69 6 q21.3 53 STAG3 68 NA NA NA NA NA NA 2.418

1 967 78 68 71

q22.1 54 GATA4 108 3.2 −1 979 NA NA NA NA NA NA 72 77 72 8 p23.1 55 VPS13E 202 3.9 1 929 NA NA NA NA NA NA 85 69 74 8 q22.2 56 DOCK5 141 5.4 −1 1000 NA NA NA NA NA NA 81 78 75 8 p21.2 57 ZHK2 218 NA NA NA 2.8 1 771 NA NA NA 82 80 78 8 q24.13 58 A

GEF5

0 NA NA NA NA NA NA 2.7472 1 750 65 10

81 7 q35 59 SDC2 193 3.4 1 991 NA NA NA HA NA NA 75 90 82 8 q22.1 60 MYIX 10 NA NA NA 8.8 1 842 NA NA NA 83 75 83 3 q21.1 61 LPHN3 23 NA NA NA NA NA NA 2.4503 −1 794 80 92 85 4 q13.1 62 MC3PD3 78 NA NA NA NA NA NA 2.3144 1 904 90 82 86 7 q22.1 63 GY

244 NA NA NA NA NA NA 2.76

−1 894 99 89 92 12 p12.1 64 GA

338 NA NA NA 2.8 −1 999 NA NA NA 84 105 95 16 q24.3 65 RAB

3

NA NA NA 3.7 1 870 NA NA NA 99 97 97 23 p22.2 66 POLR3D 127 NA NA NA 2.7 −1 955 NA NA NA 91 108 98 8 p21.3 67 PSD3 11

7.3 −1 1000 NA NA NA NA NA NA 92 104 100 8 p22 68 ZPPM2 213 4.2 1 991 6.3 1 996 NA NA NA 140 71 101 8 q23.1 69 ATP5V1C1 209 NA NA NA 2.4 1 858 NA NA NA 114 93 102 8 q22.3 70 MEF2C 38 NA NA NA NA NA NA 2.2584 −1 838 109 98 103 8 q14.2 71 PKIA 185 3.3 1 999 NA NA NA NA NA NA 115 99 104 8 q21.12 72 ADAMTS18 273 3.5 −1 902 NA NA NA NA NA NA 100 114 105 18 q23.1 73 STYXL1 65 NA NA NA NA NA NA 2.8049 1 863 104 110 106 7 q11.23 74 EPM2A 51 NA NA NA NA NA NA 2.3572 −1 990 113 10

108 6 q24.3 75 LEPREL1 19 NA NA NA 2.6 1 755 NA NA NA 106 119 110 3 q25 76 GABRA2 22 NA NA NA NA NA NA 2.2756 −1 876 119 107 111 4 p12 77 RCOR3 2

NA NA NA NA NA NA 1.7131 1 814 188 120 114 11 q12.1 78 MPHAS1 95 3.3 −1 958 NA NA NA NA NA NA 123 10

115 8 p23.1 79 SCARA5 156 3.3 −1 925 NA NA NA NA NA NA 130 101 118 8 p21.1 80 CCDC25 156 4.4 −1 996 NA NA NA NA NA NA 132 100 117 8 p21.1 81 FAM38A 323 NA NA NA 2.7 −1 885 NA NA NA 110 130 119 16 q24.3 82 CTS5 104 2.5 −1 941 NA NA NA NA NA NA 111 136 122 8 p23.1 83 PTK2 235 NA NA NA 2.3 1 654 NA NA NA 107 144 123 6 q24.3 84 SPIRE2 331 NA NA NA 1.7 −1 608 NA NA NA 124 1

124 16 q24.3 85 C13orf23 246 NA NA NA NA NA NA 2.2139 −1 748 141 113 125 13 q13.3 86 BOD1L 20 NA NA NA NA NA NA 2.3608 −1 954 129 1

126 4 p15.33 87 FAM160B2 120 2.5 −1 839 1.8 −1 587 NA NA NA 127 133 129 8 p21.3 88 NJS1 48 NA NA NA NA NA NA 2.2209 −1 958 123 139 130 8 q22.2 89 MTHPSC 309 NA NA NA 2.4 −1 824 NA NA NA 112 150 131 16 q24.1 90

208 NA NA NA 2.2 1 733 NA NA NA 122 155 135.5 8 q22.3 91 CALNS 325 NA NA NA 2.3 −1 856 NA NA NA 131 147 137 16 q24.3 92 PSTL5 38 NA NA NA NA NA NA 2.2407 −1 641 138 143 140 4 q32.2 93 SIM1 46 NA NA NA NA NA NA 2.1943 −1 839 120 145 141 6 q16.9 94 TG 231 3.3 1 997 NA NA NA NA NA NA 138 149 144 8 q24.22 95 BFSP2 12 NA NA NA 2.4 1 678 NA NA NA 139 154 148 3 q22.1 96 MMP16 194 NA NA NA 3.5 1 931 NA NA NA 158 138 149 8 q21.3 97 RIMS2 210 2 1 582 4 1 939 NA NA NA 181 141 150 5 q22.3 98 PDS58 249 NA NA NA NA NA NA 2.0408 −1 661 145 159 151 13 q13.1 99 CDK7 31 NA NA NA 2.7 −1 9

NA NA NA 158 146 153 5 q13.2 100 CNTNAP4 27

3.2 −1 825 NA NA NA NA NA NA 196 138 156 16 q23.1 101 CFDP1 274 3 −1 925 NA NA NA NA NA NA 137 137 157 16 q23.1 102

XL4 48 NA NA NA NA NA NA 1.7473 −1 537 154 167 158 6 q16.2 103 PLEX1 358 NA NA NA NA NA NA 2.3724 1

61 134 201 163 19 p13.12 104 NALCN 258 NA NA NA NA NA NA 2.18

−1 731 182 152 165 13 q33.1 105 STX1A 67 NA NA NA NA NA NA 2.17

1 835 177 161 167 7 q11.23 106 CYP7B1 182 NA NA NA 1.7 1 808 NA NA NA 147 204 168 8 q12.9 107 ARHGEF10 92 NA NA NA 2.9 −1 903 NA NA NA 215 145 171 8 q23.3 108 ENTPO4 141 2.7 −1 875 NA NA NA NA NA NA

0 1

173 8 q21.3 109 ZNF704 1

NA NA NA 2.5 1 815 NA NA NA 211 151 174 8 q21.13 110 C8orf79 105 3.9 −1 937 NA NA NA NA NA NA 163 1

176 8 p22 111 SLC9A9 13 NA NA NA 2.7 1 746 NA NA NA 170 189 177 3 q24 112 CHMF7 13

NA NA NA 2.4 −1 925 NA NA NA 185 176 178 8 p21.8 113 GPC5 296 NA NA NA NA NA NA 2.1374 −1 810 171 190 180 13 q31.9 114 MYC 2

4.2 1 972 NA NA NA NA NA NA 218 159 184 8 q24.21 115 STIP1 2

NA NA NA NA NA NA 1.7768 1 613 164 209 185 11 q13.1 116 28T820 9 NA NA NA 1.8 1 513 NA NA NA 187 184 186 3 q13.31 117 MBN

241 NA NA NA NA NA NA 2.0513 1 737 176 203 188 11 q13.1 118 SLC26A7 195 NA NA NA 2.2 1 747 NA NA NA 213 168 189 8 q21.3 119 ALCAM 8 NA NA NA NA NA NA 2.4602 1 596 194 186 191 3 q13.11 120 K

13B 160 2.7 −1 854 NA NA NA NA NA NA 188 194 192 8 p21.1 121 MBTPS1 291 2.7 −1 906 NA NA NA NA NA NA 193 182 193 16 q24.1 122 PPP2R5B 243 NA NA NA NA NA NA 1.8055 1 530 189 202 196 11 q13.1 123 VPS13C 260 NA NA NA NA NA NA 1.7860 −1 550 201 180 197 15 q22.2 124 ASPSCR1 346 NA NA NA NA NA NA 1.7035 1 549 219 178 198 17 q25.3 125 EPO

NA NA NA NA NA NA 1.9543 1 735 169 235 201 7 q22.1 126 HEY1 187 3 1 988 NA NA NA NA NA NA 206 196 203 8 q21.13 127 KALRN 11 NA NA NA 2.4 1 674 NA NA NA 197 205 204 3 q21.1 128 RGS22 203 2.7 1 956 NA NA NA NA NA NA 191 215 25 8 q22.2 129 WDR7 353 NA NA NA NA NA NA 1.9953 −1 653 200 217 210 16 q31.31 130 CO11A3 5 NA NA NA NA NA NA 1.8904 −1 5

238 206 213 1 p21.1 131 GHDC 341 NA NA NA NA NA NA 1.7583 1 523 221 218 215 17 q21.2 132 ATP2C2 295 3.5 −1 943 NA NA NA NA NA NA 216

5 216 15 q24.1 133 GDH17 196 2.8 1 976 NA NA NA NA NA NA 227 216 217 8 q22.1 134 D3K3 17 NA NA NA 1.9 1 566 NA NA NA 192 258 219 9 q27.3 135 GRK5 236 NA NA NA 2.4 −1 831 NA NA NA 210 237 220 10 q26.11 136 GRM1 52 NA NA NA NA NA NA 1.89

−1 537 179 280 223 6 q24.3 137 IMPA1 180 NA NA NA 1.9 1 647 NA NA NA 243 210 224 8 q21.13 138 RPI

176 2.3 1 813 NA NA NA NA NA NA 261 211 229 8 q21.11 139 COL81A1 38 NA NA NA NA NA NA 1.8091 −1 596 235 248 232 8 p12.1 140 COL12A1 40 NA NA NA NA NA NA 1.8241 −1 597 241 240 233 6 q14.1 141 MLYCD 289 2.4 −1 819 NA NA NA NA NA NA 234 248 234 16 q23.3 142 AR 358 2.3 1 650 2.5 1 806 NA NA NA 266 221 235 23 q12 143 PLCB1 359 NA NA NA NA NA NA 1.9352 −1 579 181 330 240 20 p12.3 144 ACTL8 3 NA NA NA 1.9 −1 682 NA NA NA 284 228 242 1 p36.13 145 TFOP1 257 NA NA NA 2.3 −1 728 NA NA NA 205 304 248 13 q34 146 ICCE 55 NA NA NA NA NA NA 1.8487 1 590 250 260 255 7 p22.2 147 SMARCB1 360 NA NA NA 1.8 −1 523 NA NA NA 239 236 256 22 q11.83 148 MTDH 199 NA NA NA 1.9 1 584 NA NA NA 225 301 259 8 q22.1 149 NECAB2 290 NA NA NA 2 −1 688 NA NA NA 255 371 262 16 q23.3 150 DEFB 334 NA NA NA 1.9 −1 678 NA NA NA 214 338 266 18 q24.3 151 PINF40 262 NA NA NA NA NA NA 2.0578 1 774 320 227 270 18 p11.2 152 TICAM2 37 NA NA NA NA NA NA 1.8257 −1 589 303 241 271 5 q22.3 153 QLC1 271 2.1 −1 642 NA NA NA NA NA NA 327 226 273 16 q22.3 154 MECOM 16 NA NA NA 2 1 587 NA NA NA 279 258 277 3 q38.2 155 TOEB1 178 1.8 1 590 NA NA NA NA NA NA 275 277 279 8 q21.11 156 CTNNA2 7 NA NA NA NA NA NA 1.8228 −1 838 391 291 280 2 p12 157 NIPAL2 200 1.9 1 654 NA NA NA NA NA NA 289 205 282 8 q22.2 158 CDCA2 146 2 −1 608 NA NA NA NA NA NA 801

283 3 p21.2 159 WWP2 267 1.3 −1 627 NA NA NA NA NA NA 251 315 284 16 q22.1 160 DDX19A 288 2.3 −1 756 NA NA NA NA NA NA 220 383 295 16 q22.1 161 BTK3 201 1.8 1 614 NA NA NA NA NA NA 265 309 267 8 q22.2 162 DNAH2 337 1.8 −1 541 NA NA NA NA NA NA 247 332 288 17 p13.1 163 NFA15 266 3.3 −1 760 NA NA NA NA NA NA 336 254 291 16 q22.1 164 CNG81 263 1.8 −1 524 NA NA NA NA NA NA 297 280 292 16 q13 165 UB

P 41

−1 891 NA NA NA NA NA NA 258 335 293 6 q14.1 166 C8orf16 90 2.2 −1 725 NA NA NA NA NA NA 285 293 294 8 p23.1 167 KIAA0186 220 2.3 1 819 NA NA NA NA NA NA 253 334 296 8 q24.13 168 CLONKB 1 NA NA NA NA NA NA 2.0014 1 746 276 307 297 1 p36.13 169 C16orf80 258 2.2 −1 577 NA NA NA NA NA NA 381 302 298 16 q21 170 ZFHK3 270 2.2 −1 656 NA NA NA NA NA NA 313 273 299 16 q22.3 171 PPM1L 15 NA NA NA 2 1 628 NA NA NA 370 329 303 8 q24.1 172 NKIRAS2 303 NA NA NA NA NA NA 1.9534 1 579 295 299 304 17 q21.2 173 RSPC2 215 1.8 1 550 NA NA NA NA NA NA 306 292 305 8 q23.1 174 XPO2 119 2.3 −1 738 NA NA NA NA NA NA 329 272 306 8 p21.3 175 MEI 42 2.5 −1 728 NA NA NA NA NA NA 262 321 307 6 q14.2 176 NLGN

Y 390 NA NA NA NA NA NA 2.4189 −1 734 339 275 312 24 q11.221 177 LXY81 118 2 −1 848 NA NA NA NA NA NA 300 315 316 8 p21.3 178 FBXL18 56 NA NA NA NA NA NA 1.8546 1 652 323 294 317 7 p22.1 179 TBC1D108 281 NA NA NA NA NA NA 1.8343 1 573 372 347 321 15 p11.2 180 WFOR88 272 2.1 −1 658 NA NA NA NA NA NA 304 330 322 16 q23.1 181 BLK 101 2.1 −1 671 NA NA NA NA NA NA 315 314 325 8 p23.1 182 MERCE 71 NA NA NA NA NA NA 2.1134 1 782 350

327 7 q22.1 183 DLGAP2 91 NA NA NA 2.2 −1 662 NA NA NA 360

330 8 p23.3 184 2FAT 234 2.5 1 795 NA NA NA NA NA NA 325 317 331 8 q24.22 185 FASN 348 NA NA NA NA NA NA 3.0027 1 863 296 356 332 17 q25.3 186 GIGYP1 81 NA NA NA NA NA NA 2.7127 1 957 335 311 335 7 q22.1 187 ANKA13 219 2.1 1 682 NA NA NA NA NA NA 310 345 336 8 q24.13 188 CDYL2 280 2.5 −1 699 NA NA NA NA NA NA 316 351 339 16 q23.2 189 TOX 181 4.3 1

NA NA NA NA NA NA 338 3

349 8 q12.1 190 NKX2-6 143 2.4 −1 870 NA NA NA NA NA NA 340 366 357 8 p21.2 191 RALYL 191 2.3 1 935 NA NA NA NA NA NA 345 362 369 8 q21.2 192 TBC1D22A 361 NA NA NA 4.6 −1 999 NA NA NA 387 346 368 22 q13.31 193 TFE3 363 NA NA NA 2.1 1 991 NA NA NA 362 353 364 23 p11.23 194 KCNAB1 14 NA NA NA 5.5 1 996 NA NA NA 383 367 367 5 q25.31 195 SULP1 166 5.2 1 1000 3.4 1 994 NA NA NA 3 4 3 8 q12.2 196 RA65C 342 NA NA NA NA NA NA 3.5399 1 993 6 3 5 17 q21.2 197 DHK56 239 NA NA NA NA NA NA 8.9116 1 952 14 16 18 17 q21.2 198 ASAP1 238 NA NA NA 3.6 1 974 NA NA NA 21 23 20 8 q24.21 199 CASA 313 2.6 −1 632 3.8 −1 955 NA NA NA 23 28 28 18 q24.2 200 C6orf19 53 NA NA NA NA NA NA 2.7921 −1 976 36 36 36 6 q27 201 NCOA2 169 3.2 1 997 2.4 1 806 NA NA NA 35 40 37 8 q13.3 202 PLD1L2 283 4.9 −1 999 2 −1 715 NA NA NA 41 45 42 16 q23.2 203 BANF 314 2.6 −1 901 3.3 −1 857 NA NA NA 42 49 46 18 q24.2 204 KIAA1967 133 2.8 −1 925 3.1 −1 980 NA NA NA 50 57 52 8 p21.3 205 CCPG2 29 NA NA NA NA NA NA 3.1195 1 936 56 52 53 7 q32.2 206 ZNF708 205 NA NA NA 2.8 1 889 NA NA NA 53 56 54 8 q22.3 207 GAN 285 2.7 −1 869 2.4 −1 902 NA NA NA 49 61 55 16 q23.2 208 FLCG2 266 2.8 −1 838 2.7 −1 913 NA NA NA 61 50 56 16 q23.2 209 C18orf57 346 NA NA NA NA NA NA 2.7943 1 952 58 58 59 19 p13.12 210 PSGFRL 111 4.8 −1 898 NA NA NA NA NA NA 62 55 60 8 p22 211 ESD 249 NA NA NA NA NA NA 2.5790 −1 973 65 59 62 13 q14.2 212 CPA5 55 NA NA NA NA NA NA 2.7823 1 924 70 36 67 7 q32.2 213 BIN3 134 1.7 −1 507 2.8 −1 992 NA NA NA 71 73 70 8 p21.3 214 ZFHX4 104 4.9 1 1000 NA NA NA NA NA NA 74 76 73 8 q21.11 215 DPA8 163 3.6 1 1000 NA NA NA NA NA NA 77 81 75 8 q12.2 216 EYA1 172 3.4 1 997 NA NA NA NA NA NA 73 89 77 8 q18.3 217 CHRNA2 153 3.2 −1 999 NA NA NA NA NA NA 75 87 79 8 p21.2 218 TNKS 97 4 −1 1000 NA NA NA NA NA NA 87 54 84 8 p23.1 219 HNF43 183 4.1 1 1000 NA NA NA NA NA NA 103 72 87 8 q21.11 220 LRCH1 243 NA NA NA NA NA NA 2.3847 −1 801 29 94 88 13 q14.13 221 ACRA1A 149 9.9 −1 991 NA NA NA NA NA NA 96 79 89 8 p21.2 222 EPHX2 154 3.3 −1 992 NA NA NA NA NA NA 89 88 90 8 p21.1 223 SOR353 130 NA NA NA 3 −1 957 NA NA NA 83 95 91 8 p21.3 224 GRIA2 27 NA NA NA NA NA NA 2.2933 −1 843 89 96 93 1 q32.1 225 POLIM2 131 NA NA NA 2.9 −1 983 NA NA NA 94 91 94 8 p21.3 226 MTMFP 109 3.7 −1 971 NA NA NA NA NA NA 86 106 96 8 p22 227 FBXO94 75 NA NA NA NA NA NA 2.4831 1 817 118 85 99 7 q22.1 228 CRISPLD1 182 4.9 1 1000 NA NA NA NA NA NA 96 124 107 8 q21.11 229 CPYS 211 3.2 1 978 NA NA NA NA NA NA 92 129 109 8 q22.3 230 DTNA 381 NA NA NA NA NA NA 2.2378 −1 734 102 125 112 18 q12.1 231 KLHDC4 311 NA NA NA 2.5 −1 987 NA NA NA 118 111 113 18 q24.2 232 CYRA 318 NA NA NA 2.9 −1 941 NA NA NA 117 121 118 18 q24.3 233 JPH3 310 2.4 −1 968 2.4 −1 908 NA NA NA 101 142 120 18 q24.2 234 TMEM120A 64 NA NA NA NA NA NA 1.7993 1 511 128 115 121 7 q11.23 235 MTUS1 112 3.6 −1 976 NA NA NA NA NA NA 143 116 127 8 p22 236 C8orf34 165 6 1 1000 NA NA NA NA NA NA 128 132 128 8 q13.2 237 GRHL2 208 NA NA NA 2.4 1 790 NA NA NA 125 140 132 8 q22.3 238 CPA2 83 NA NA NA NA NA NA 2.1399 1 717 158 117 138 7 q32.2 239 NAT2 115 3.3 −1 993 NA NA NA NA NA NA 140 194 134 8 p22 240 DPYSL2 143 3.3 −1 987 NA NA NA NA NA NA 155 128 135.5 8 p21.2 241 ZDHHG7 303 NA NA NA 2.5 −1 839 NA NA NA 159 128 138 16 q24.1 242 ELP3 158 3.1 −1 939 NA NA NA NA NA NA 166 119 139 8 p21.1 243 FRICETB2 138 NA NA NA 1.7 −1 501 NA NA NA 133 180 142 8 p21.3 244 NBL2 103 2.7 −1 921 NA NA NA NA NA NA 150 130 143 8 p23.1 245 HR 122 NA NA NA 2.7 −1 895 NA NA NA 188 112 145 8 p21.3 246 EPR3A 228 3.1 1 985 NA NA NA NA NA NA 144 148 146 8 q24.22 247 STMN4 150 3.3 −1 994 NA NA NA NA NA NA 162 131 147 8 p21.2 248 PROM14 168 4.7 1 996 NA NA NA NA NA NA 135 171 152 8 q13.8 249 MARVELD2 35 NA NA NA 3 −1 966 NA NA NA 142 164 154 5 q13.2 250 SLCSGA14 128 1.8 −1 560 2.2 −1 791 NA NA NA 152 160 155 6 p21.3 251 ACTL6B 80 NA NA NA NA NA NA 1.7362 1 593 163 158 159 7 q22.1 252 TUSC3 103 3.1 −1 945 NA NA NA NA NA AN 157 170 160 8 p22 253 COXANE 305 NA NA NA 3.5 −1 938 NA NA NA 148 181 161 16 q24.1 254 XKR9 171 2.7 1 929 NA NA NA NA NA NA 165 163 162 8 q13.3 255 C16orf46 281 NA NA NA 2.2 −1 768 NA NA NA 151 183 164 16 q23.2 256 TAF9 33 NA NA NA 2.6 −1 963 NA NA NA 175 162 166 5 q13.2 257 KCNG3 225 6 1 1000 NA NA NA NA NA NA 167 180 169 8 q24.22 258 UTRN 50 NA NA NA NA NA NA 2.3296 −1 766 174 174 170 6 q24.2 259 RAD17 34 NA NA NA 2.5 −1 989 NA NA NA 172 182 172 5 q13.2 260 ZFFM1 315 NA NA NA 2.5 −1 924 NA NA NA 146 219 175 16 q24.2 261 PTCSS1 197 2.5 1 874 NA NA NA NA NA NA 184 177 179 8 q22.1 262 IRP8 307 NA NA NA 2.5 −1 976 NA NA NA 199 169 181 16 q24.1 263 YWHAZ 204 NA NA NA 2.2 1 722 NA NA NA 204 160 182 8 q22.3 264 MRP538 30 NA NA NA 2.6 −1 982 NA NA NA 195 175 183 5 q13.2 265 LACTB2 170 2.6 1 932 NA NA NA NA NA NA 160 223 187 8 q13.2 266 SNA13 321 NA NA NA 2.4 −1 914 NA NA NA 231 156 190 16 q24.3 267 TMEM71 229 2.9 1 958 NA NA NA NA NA NA 150 207 194 8 q24.22 268 PREX2 164 7.5 1 1000 NA NA NA NA NA NA 190 199 195 8 q13.2 269 CPA1 26 NA NA NA NA NA NA 3.0583 1 715 228 173 199 7 q32.2 270 PGF20L1 220 2.8 1 901 NA NA NA NA NA NA 198 280 200 8 q24.22 271 KIAA0513 301 NA NA NA 2.1 −1 816 NA NA NA 212 189 202 16 q24.1 272 R15 181 8 1 991 NA NA NA NA NA NA 238 179 206 8 q21.11 273 PCM1 113 1.7 −1 529 NA NA NA NA NA NA 183 204 207 8 p22 274 SH204A 117 2.9 −1 908 NA NA NA NA NA NA 249 172 208 8 p21.3 275 C16orf74 304 NA NA NA 2.3 −1 939 NA NA NA 202 214 209 16 q24.1 276 TPB3 18 NA NA NA 3 1 822 NA NA NA 203 228 211 8 q23 277 DACH1 258 NA NA NA NA NA NA 1.8675 −1 570 252 185 212 13 q21.33 278 TNFR8F10A 139 NA NA NA 2.2 −1 774 NA NA NA 245 196 214 8 p21.3 279 MDH2 66 NA NA NA NA NA NA 1.9563 1 728 238 208 218 7 q11.23 280 PAG1 139 NA NA NA 2 1 776 NA NA NA 173 250 221 8 q21.13 281 SLC25A37 142 2.6 −1 845 NA NA NA NA NA NA 226 222 222 8 p21.2 282 BCAR1 273 2.5 −1 846 NA NA NA NA NA NA 240 213 225 16 q23.1 283 COX411 306 NA NA NA 2.6 −1 911 NA NA NA 178 289 226 16 q24.1 284 EIF4H 59 NA NA NA NA NA NA 2.0065 1 775 224 236 227 7 q11.23 285 ZC3H13 317 NA NA NA 2.1 −1 878 NA NA NA 217 244 228 18 q24.2 286 STMN2 188 2.8 1 962 NA NA NA NA NA NA 334 196 230 8 q21.13 287 AFG3L1 335 NA NA NA 2.3 −1 947 NA NA NA 254 224 231 18 q24.3 288 HS017B2 287 2.6 −1 701 NA NA NA NA NA NA 229 259 236 16 q22.3 289 MYO 230 NA NA NA 2.3 −1 901 NA NA NA

208 237 16 q24.3 290 DLC1 106 6.5 −1 1000 NA NA NA NA NA NA 207 298 238 8 p22 291 EPHA7 44 NA NA NA NA NA NA 1.7756 −1 529 237 252 239 6 q16.1 292 TRIM35 154 2.5 −1 926 NA NA NA NA NA NA 209 287 241 8 p21.2 293 LRRC56 280 2.4 −1 830 NA NA NA NA NA NA 232 252 243 16 q24.1 294 CNG83 192 1.8 1 534 NA NA NA NA NA NA 319 191 244 8 q21.3 295 ASCC3 47 NA NA NA NA NA NA 1.7954 −1 536 246 248 245 6 q16.3 296 FIFC2 61 NA NA NA NA NA NA 1.8989 1 625 208 235 246 7 q11.23 297 CLEC3A 278 2.3 −1 781 NA NA NA NA NA NA 287 252 247 18 q23.1 298 IL17C 318 NA NA NA 1.8 −1 639 NA NA NA 244 256 249 16 q24.3 299 BMP1 125 NA NA NA 2.2 −1 918 NA NA NA 259 342 250 8 p21.3 300 CFA4 64 NA NA NA NA NA NA 1.9432 1 632 242 281 251 7 q32.2 301 CC90 227 1.9 1 640 NA NA NA NA NA NA 262 243 252 8 q24.22 302 HEPH 364 1.2 1 537 NA NA NA NA NA NA 292 220 253 23 q12 303 LRP12 212 NA NA NA 2 1 635 NA NA NA 277 233 254 8 q22.3 304 AGFG2 74 NA NA NA NA NA NA

1 743 317 213 257 7 q22.1 305 TRPA1 174 2.3 1 808 NA NA NA NA NA NA 257 263 258 8 q13.3 306 GRNS2 303 NA NA NA 2.1 −1 881 NA NA NA 258 253 260 16 q24.1 307 CENPH 29 NA NA NA 1.9 −1 693 NA NA NA 288 233 261 5 q13.2 308 KLHL38 397 NA NA NA 1.8 −1 606 NA NA NA 229 312 263 16 q24.1 309 ARHGBPOIU 2 NA NA NA 2.1 −1 730 NA NA NA 258 263 264 1 p38.13 310 TRAPPC2L 328 NA NA NA 1.9 −1 670 NA NA NA 362 230 265 16 q24.3 311 TCF25 332 NA NA NA 2.1 −1 821 NA NA NA 372 264 267 16 q24.3 312 TNFRSF180 137 1.9 −1 608 NA NA NA NA NA NA 288 250 268 8 p21.3 313 MYOM3 93 2.1 −1 705 NA NA NA NA NA NA 295 345 269 8 p23.3 314 GCSH 282 NA NA NA 1.9 −1 673 NA NA NA 248 296 272 18 q23.2 315 KIAA1809 298 NA NA NA 1.9 −1 641 NA NA NA 260 294 274 16 q24.1 316 FANCA 330 NA NA NA 1.9 −1 618 NA NA NA 299 247 275 16 q24.3 317 ER

96 1.9 −1 607 NA NA NA NA NA NA 312 236 276 8 p23.1 318 HSOL1 296 NA NA NA 2 −1 885 NA NA NA 273 278 278 16 q24.1 319 KIAA0182 302 NA NA NA 2 −1 781 NA NA NA 305 251 281 16 q24.1 320 CBFA2T3 327 NA NA NA 1.8 −1 893 NA NA NA 274 297

15 q24.3 321 EGR3 135 NA NA NA 2 −1 751 NA NA NA 308 269 289 8 p21.3 322 PCOLCE 77 NA NA NA NA NA NA 1.8050 1 608 294 281 290 7 q22.1 323 C16orf85 316 NA NA NA 2.1 −1 801 NA NA NA 290 291 295 16 q24.2 324 HMBOX1 159 1.8 −1 553 NA NA NA NA NA NA 287 306 300 8 p21.1 325 MTMP8 100 1.9 −1 674 NA NA NA NA NA NA 343 257 301 8 p33.1 326 MSC 173 2 1 625 NA NA NA NA NA NA 291 308 302 8 q18.3 327 ST3GAL2 2

2.4 −1 774 NA NA NA NA NA NA 259 340 308 18 q22.1 328 FOXF1 508 NA NA NA 2.2 −1 894 NA NA NA 344 270 309 16 q24.1 329 C8orf58 132 NA NA NA 3 −1 999 NA NA NA 384 270 310 8 p21.3 330 KTC09 145 2 −1 663 NA NA NA NA NA NA 271 344 311 8 p21.2 331 ANGPT1 214 2.4 1 818 NA NA NA NA NA NA 388 252 313 8 q23.1 332 GDAP1 180 2 1 883 NA NA NA NA NA NA 283 335 314 8 q21.11 333 RNF165 329 NA NA NA 2.2 −1 877 NA NA NA 263 360 315 16 q24.3 334 KLHL1 258 NA NA NA NA NA NA 1.8837 −1 608 298 325 318 13 q21.33 335 LOXL2 140 NA NA NA 1.9 −1 675 NA NA NA 322 298 319 8 p21.3 336 WISP1 233 2.2 1 777 NA NA NA NA NA NA 280 343 320 8 q24.22 337 C8orf80 157 3.8 −1 857 NA NA NA NA NA NA 357 274 323 8 p21.1 338 LAT2 60 NA NA NA NA NA NA 1.8646 1 697 328 302 324 7 q11.23 339 USP10 29

2.3 −1 891 NA NA NA NA NA NA 321 313 325 18 q24.1 340 CDH15

NA NA NA 1.9 −1 673 NA NA NA 300 303 328 18 q24.3 341 WFOC1 294 2.3 −1 713 NA NA NA NA NA NA 311 327 329 16 q24.1 342 C7orf51 73 NA NA NA NA NA NA 2.1914 1 773 307 339 333 7 q22.1 343 EPB2 147 5.1 −1 999 NA NA NA NA NA NA 309 337 334 8 p21.2 344 CODC125 32 NA NA NA 2 −1 721 NA NA NA 336 319 337 5 q13.2 345 LGB 124 NA NA NA 2 −1 676 NA NA NA 382 328 338 8 p21.3 346 NUGT1B 121 NA NA NA 2.3 −1 786 NA NA NA 314 354 340 8 p21.3 347 PHYH1P 125 NA NA NA 2.2 −1 860 NA NA NA 361 306 341 6 p21.3 348 PILRA 70 NA NA NA NA NA NA 1.8998 1 701 368 318 342 7 q22.1 349 KAT2A 343 NA NA NA NA NA NA 3.1975 1 9

318 357 343 17 q21.2 350 CSMD8 216 4.8 1 938 4.2 1 809 NA NA NA 351 384 344 8 q22.3 351 REEP4 123 NA NA NA 2.5 −1 847 NA NA NA 324 352 345 8 p21.3 352 TUBB3 333 NA NA NA 2.6 −1 843 NA NA NA 348 328 346 18 q24.3 353 CDT1 324 NA NA NA 2 −1 745 NA NA NA 365 313 347 16 q24.3 354 EDA2R 385 2 1 829 NA NA NA NA NA NA 349 331 348 23 q12 355 DUS1L 347 NA NA NA NA NA NA 2.2705 1 904 364 321 350 17 q25.3 356 LRCH4 75 NA NA NA NA NA NA 2.2504 1 851 342 349 351 7 q22.1 357 TMEM75 223 3.5 1 992 NA NA NA NA NA NA 337 356 352 8 q24.21 358 NUDT7 277 2.2 −1 730 NA NA NA NA NA NA 358 338 359 16 q23.1 359 TSGA14 67 NA NA NA NA NA NA 9.3754 1 966 354 341 354 7 q32.2 360 CDC42BPG 242 NA NA NA NA NA NA 3.3279 1 813 360 338 355 11 q13.1 361 TSC22D4 72 NA NA NA NA NA NA 2.1304 1 867 341 359 356 7 q22.1 362 NOTUM 345 NA NA NA NA NA NA 2.6758 1 983 358 348 358 17 q25.3 363 HSPB8 341 NA NA NA NA NA NA 2.9366 1 957 346 361 360 17 q21.2 364 TFR2 79 NA NA NA NA NA NA 2.8230 1 960 352 356 361 7 q22.1 365 SLA 232 2.2 1 7

6 NA NA NA NA NA NA 347 385 362 8 q24.22 366 WWOX 279 9.3 −1 1000 NA NA NA NA NA NA 359 364 365 16 q23.1 367 POU5F1B 221 2.9 1 9

NA NA NA NA NA NA 366 356 366 8 q24.21 368 OPHN1 367 5.8 1 889 NA NA NA NA NA NA 368 368 368 22 q12 1b Final- min-dist- Index0- NYU- MSKa1- MSKa2- RANK gene gene-start gene-end genesBt

n confg slump-index dstorev dstnext to-RGL Proxy 1 Zadjust Zadjust Zadjust 1 PPP3CC 22354541 22454580 0 1 26 10616 −7079 −7079 1 0.52 0.29 NA 2 SLCO5A1 70747128 70908782 0 1 33

1661

−11428 −11428 1 1.63 1.16 NA 3 SLC7A6 86421131 86480615 0 1 68 18511 −84

18511 1 0.00 0.47 NA 4 SLC7A

173

975 17472357 0 1 31 60

−

68 6065 1 1.10 NA NA 5 CRISPLD8 83411113 88600614 0 1 68 64950 −40087 −40087 1 0.25 0.42 NA 6 CDH13 814

751 8

7705 1 0 NA 102

−790123 102502 1 3.67 0.42 NA 7 CDH8 60244888 66628240 82 0 NA 7528058 −3524089 −3524069 1 NA NA 0.87 8 CDH2 23784

4 24011188 19 0 NA 5673873 NA 5672873 1 NA NA 0.70 9 ASAH1 179

214 17986787 1 1 22 306

8 −22550 −22652 1 3.10 NA NA 10 KCN62 738

24 7401

1 1 34 352193 −492151 352193 1 2.91 NA NA 11 KCNH4 375

38 3758

1 1 54 7810 −1591 −1891 1 NA NA 0.88 12 KCTD8 43870888 44146581 3 0 NA 1800780 −30632267 1800

60 1 NA NA 0.38 13 JPH1 753

3 753

117 0 1 35 29056 −262534 29056 1 2.37 NA NA 14 MEST 128813282 120633368 0 1 13 41 −45149 41 1 NA NA 0.58 15 NCALD 102767947 103205

1 1 1 40 128437 −16952 −16952 1 2.03 0.42 NA 16 COL19A1 70

169 70973878 20 0 NA 4871884 NA 4821584 NA NA 0.70 17 MAP3K7 91282074 913536

0 1 5 2654235 −70

575 2654235 1 NA NA 0.56 18 YWHAG 75794353 7

52 120 0 NA 23787

−260189 −350189 1 NA NA 0.34 19 NOL4 29

30057513 0 1 67 269786 −563873 289755 1 NA NA 0.98 20 ENOX1 42685704 43259044 18 0 NA 2766260 −4175452 2766260 1 NA NA 2.12 21 CSMD1 27802

32589

46 1 14 5420413 −899503 −699503 1 NA NA 1.44 22 SGCZ 19991744 15140219 0 1 20 301

2 −574978 301382 1 1.49 NA 0.74 23 PDE10A 1

165998578 NA 1 8 NA −17688 −17865 1 NA NA 1.49 24 PCDH8

774970 667

7

0 1 43 24701

8 −813

50 2470148 1 NA NA 1.38 25 HTR2A 48305814 46388178 44 1 48 12763542 −36148 −38146 1 NA NA 0.82 26 HIP1 75001345 75286216 5 0 NA 248823 −1543149 245023 1 NA NA 1.32 27 CC220 86081176 65776140 NA 0 NA NA −125331

−12833136 1 NA NA 0.63 28 DCC 43121158 40311780 10 0 NA 3157834 −17395350 3157934 1 NA NA 2.79 29 CC2D1A 13878014 13902891 1 1 88 30662 −105 −106 1 NA NA 1.02 30 PTK28 272

818 27372620 0 1 30 375 −185 −158 1 3.04 NA NA 31 BCMO1 79828797 79882

48 0 1 53 23828 −1

320 −18320 1 0.42 0.55 NA 32 MACROO1 6352260

63690109 1 0 NA 19764 −

1715 19764 1 NA 0.08 0.41 33 GRID2 93444531

014730 186 0 NA 60480408 −30

−30

240

1 NA NA 1.77 34 DIAPH3 69137718 59836120 2 0 NA 6138850 −12769542 6138850 1 NA NA 0.60 35 PILRB

9771672

0 1 11 5618 −111895

616 1 NA NA 0.44 36 M

S2 94970919 35189740 193 0 NA 24742144 NA 24742144 1 NA NA 1.00 37 MSRA 994912

9 10323

03 4 1 15 897587 −271923 −271923 1 1.75 NA NA 38 DPYD 87315890 98159203 18 0 NA 4955408 −79289745 4965408 1 NA NA 0.41 39 ANKRD11 87881536 88084470 11 1 81 246990 −72130 −72136 1 0.47 0.85 NA 40 NRXN1

148 51113178 155 0 NA 28619013 NA 28619013 1 NA NA 0.59 41 ADCY8 131861736 132123864 0 1 45 861683 −378337 −

8237 1 0.52 1.97 NA 42 TRDN 123579182 12

7 96 0 NA 20654629 −5440605 −5440605 1 NA NA 0.48 43 STRJ8 74495180 74821629 1 0 NA 199555 −119303 −119303 1 1.43 NA NA 44 SP1 64

64302817 1 0 NA 24747 −680058 24747 1 NA NA 0.23 45 CLIP2 73341739 73458195 15 1 9 1543149 −35035 −35035 1 NA NA 0.52 46 CLDN3 72821263 72822636 6 0 NA 404089 −49338 −49338 1 NA NA 0.29 47 ZSWIM

13767274 13804044 1 0 NA 50124 NA 50124 1 NA NA 0.38 48 GLRB 186216788 158312299 0 1 3 48887 −2584470 48887 1 NA NA 0.31 49

S2 15637513

155632318 14 0 NA 2584470 −50450408 3524470 1 NA NA 0.37 50 TRPS1 1164

900 116750428 20 1 43 7112853 −1971482 −1971482 1 0.42 0.33 NA 51 MCGA2 46379043 47213

03 NA NA NA NA NA NA 1 NA NA 0.39 52 CNBD1 27947840

435230 1 1 38

3360 −122823 −122523 1 0.91 0.91 NA 53 STAG3 99613474

65

78 2 0 NA 111

5 −237872

111825 1 NA NA 0.21 54 GATA4 11599162 11654918 0 1 18 9709 −139640 9709 1 0.57 NA NA 55 VPS12B 100094670 100958283 1 0 NA 83462 −187596 83469 1 0.98 NA NA 56 DOCK3 25098204 2532

36 2 0 NA 14747 −1478148 14747 1 1.97 NA NA 57 ZHX2 123263082 124055

9 0 NA 706

0 −7112553 706830 1 NA 0.29 NA 58

143683386 14370

NA 0 NA NA −13747479 −13747479 1 NA NA 0.35 59 SDC2 97575058 97693213 1 1 39 1032170 −159108 −159108 1 0.66 NA NA 60 MYLK 12

811586 125

2 0 NA 210407 −5462769 21040

1 NA 0.58 NA 61 LPHN3 62045434 62620762 167 0 NA 30824089 NA 30824068 1 NA NA 0.24 62 MOSPD3 100047661 100050932 0 1 12 5043 −3920 −3929 1 NA NA 0.17 63 GYS2 2153

90 21649048 NA NA NA NA NA NA 1 NA NA 0.36 64 GA38 88616509 8883

0 NA 0 NA NA −21819 −21813 1 NA 0.42 NA 65 RAB

A 13617262 13637

81 191 0 NA 351549

NA 35154932 1 NA 0.85 NA 66 POLR3D 22158564 22164624 1 1 26 116113 −12768 −12768 1 NA 0.83 NA 67 PSD3 184290

18915476 0 1 23 300007 −126090 −125090 1 3.23 NA NA 68 ZFPM2 106400323 106835089 2 1 41 1444960 −729979 −729079 1 1.18 2.58 NA 69 ATPBV1C1 104102424 104154481 5 0 NA 427

0 −508753 427830 1 NA 0.21 NA 70 MEF2C 880

922 88214780

3 0 NA 26727467 −19278276 −18278276 1 NA NA 0.15 71 PKIA 79590891 79678040 2 0 NA 1007876 −1648816 1007876 1 0.63 NA NA 72 ADAM1S15 75

73527 78026512 0 1 52 287400 −722891 287400 1 0.74 NA NA 73 STYXL1 75463592 75515

0 1 10 72 −1879 72 1 NA NA 0.17 74 EPM

A 1459

141 1

2 1 7 2919

7 −7722

2 291

7 1 NA NA 0.20 75 LEPREL1 191157213 191321407 NA 1 2 NA −49278 −49278 1 NA 0.29 NA 76 GABRA2 45946341 4

NA 0 NA NA −1900750 −1900750 1 NA NA 0.16 77 RCOR2 6343

303 63440892 3 0 NA 81715 NA 81715 1 NA NA 0.00 78 MFHAS1

79409 3788541 0 1 15 109015 −5420413 109315 1 0.63 NA NA 79 SCARA5 27783672 27906117 0 1 31 29490 −97583 29400 1 0.53 NA NA 80 CCDC25 27

758 27

2 0 NA 97583 −182353 97583 1 1.28 NA NA 81 FAM38A 87309616 87330317 0 1 52 67570 −2604 −2604 1 NA 0.33 NA 82 CTSB 11737442 11263058 7 0 NA 1384499 −55179 −55179 1 0.38 NA NA 83 PTK2 141727683 142080514 NA 0 NA NA −5843220 −5943220 1 NA 0.17 NA 84 SPIRE2 88472408

0 1 52 2292 −11842 2292 1 NA 0.00 NA 85 C13orf23 3

38510252 21 0 NA 4176452 −6231845 4176452 1 NA NA 0.14 86 BOD1L 13179464 13239428 76 0 NA 30632257 NA 30532257 1 NA NA 0.19 87 FAM160B2 22

28017835 0 1

5493 −52813 9490 1 0.25 0.02 NA 88 NUS1 118103310 11813857 15 0 NA 5440605 −16667349 5440805 1 NA NA 0.14 89 MTHPSO 95121204 85157609

1 57

5491 −18714 −18714 1 NA 0.21 NA 90 UBRS 103334748

0 NA 808753 −128437 −128437 1 NA 0.14 NA 91 GALNS 87407544 87450835 0 1 60 128 −4479 122 1 NA 0.17 NA 92 PSTL5 1

2524

01

NA 0 NA NA −4017824 −4013524 1 NA NA 0.15 93 SIM1 1

0939506 10

19454 0 1 5 43297 −1437836 43297 1 NA NA 0.13 94 TG 133948

7 134218306 0 1 46 −08170 −18153 −18150 1 0.01 NA NA 95 BFSP2 134601480 134576246

0 NA

90009 − 3628754 −867

54 1 NA 0.21 NA 96 MMP16 89118680 89408533 9 0 NA 2921359 683960 −683360 1 NA 0.74 NA 97

MS2 104582291 10

1 0 NA 127568 427830 127558 1 0.07 1.04 NA 98 PD85B 32058564 32250157 21 0 NA 6231848 NA 6201846 1 NA NA 0.08 99 CDK7 68586471 58800004 0 1 4 3274 11218 3274 1 NA 0.33 NA 100 CNTNAP4 74868677 75150638 1 0 NA 7

891 −845789 7

891 1 0.57 NA NA 101 CFDP1 7388510

74024888 7 1 51 843789 −25857 −25667 1 0.47 NA NA 102 FBXL2 99428055 99502570 7 0 NA 1237005 −5242062 1437006 1 NA NA 0.01 103 RPX1 13

13979097 NA 0 NA NA −30562 −30662 1 NA NA 0.13 104 NALCN 100804181 100855814 42 0 NA 17420

3 −8187438 −9187438 1 NA NA 0.13 105 STX1A 72781472 72771625 1 0 NA 49338 NA 49338 1 NA NA 0.13 106 CYP281

65873902 21 0 NA 2823081 −5476925 2623061 1 NA 0.00 NA 107 ARHGEF10 1759549 1894206 1 0 NA

−115501 2635

1 NA 0.42 NA 108 ENTPO4 2

23371081 0

28

1287 18281 14281 1 0.33 NA NA 109 ZNF704 81713324 21948571 0 1 37

−870571 83094 1 NA 0.25 NA 110 C8orf79 12847554 12931652 0 1 12 52890 −1084499 53590 1 0.42 NA NA 111 SLC9A8 1

4466755 145049928 50 0 NA 1227116 −8790009 −9790009 1 NA 0.33 NA 112 CHMP7 23157095 23175450 1 1 27 94647 −18511 −18511 1 NA 0.21 NA 113 GPC5 90848919 92916693 29 0 NA 8

87438 −

950958

8187438 1 NA NA 0.11 114 MYC 128818852 128822863 0 1 44 208193 318241 208193 1 1.16 NA NA 115 STIP1 83709879 53729596 26 0 NA 560066 −19784 −18764 1 NA NA 0.01 116 ZBTB20 115540280 116348817 51 0 NA 3482769 −8761797

769 1 NA 0.02 NA 117 MBN1 843

564 54335342 0 1 47 12948 −24747 128813 1 NA NA 0.08 118 SLC26A7 92330692

2479664 8 0 NA

29012 −2921559 2729012 1 NA 0.14 NA 119 ALCAM 106508403 106778433 49 0 NA 8701782 NA 8761787 1 NA NA 0.23 120 RIF138 28980715 29176529 NA 1 32 NA −14009 −14009 1 0.33 NA NA 121 MBTPSI 82644872 82708018 0 1 54 5371 −50994 5371 1 0.33 NA NA 122 PPP2R5B 644

8756 64458523 NA 0 NA NA −80139 −80139 1 NA NA 0.02 123 VSP13C 59931884 60139838 NA 0 NA NA −24742144 −24742144 1 NA NA 0.02 124 ASPSCR1 77528715 77860889 6 1 68 40474 −18362 −18362 1 NA NA 0.01 125 EPO 100158359 100159257 145 0 NA 2953

82 −31553 −31553 1 NA NA 0.07 126 HEY1 80838801 80842683 3 1 36 370871 −97933 −97933 1 0.47 NA NA 127 KALRN 125296278 129922728 26 0 NA 3673254 −320508 −210407 1 NA 0.21 NA 128 RGB22 101042482 101187520 7 0 NA 812460 −83169 −83463 1 0.33 NA NA 129 WDR7 524

14 50843040 45 0 NA 12883

85 −3157834 −3157834 1 NA NA 0.07 130 COL11A1 103114611 10334640 NA 0 NA NA −4956408 −4955408 1 NA NA 0.04 131 GHOC 37594832 87599722 482 0 NA 39903967 −7810 7810 1 NA NA 0.01 132 ATP

2 52958534 83055293 0 1 65 13315 −38746 13315 1 0.30 NA NA 133 CDH17 95208556 9528998

14 0 NA 2053354 −2729012 2063354 1 0.38 NA NA 134 CGKG 187347686 187862717 23 0 NA 3268193 −17000632 3259103 1 NA 0.06 NA 135 GRK5 120957091 121205118 NA NA NA NA NA NA 1 NA 0.21 NA 136 GRM1 146390611 146

004

7

3 0 NA 18812721 −291927 −291927 1 NA NA 0.04 137 IMFA1 82732751 52781118 4 0 NA 2842997 −545893 −545893 1 NA 0.05 NA 138 RPL7 74365073 74375857 1 0 NA 119003 −352193 119303 1 0.17 NA NA 139 OCL21A1

8029347 5638

1 NA NA NA NA NA NA 1 NA NA 0.09 140 OCL18A1 75850782 75972343 18 0 NA 7586493 −4871884 −4871884 1 NA NA 0.08 141 MLYCD 82490231 82607286 1 0 NA 82452 −102526 52452 1 0.21 NA NA 142 AR 66680599 86850844 0 1 69 318596 #z,899;34991 318598 1 0.17 0.29 NA 143 FLCB1 8061296

81350 NA NA NA NA NA NA 1 NA NA 0.05 144 ACTL8 17954395 18025145 682 1 1 79289745 −57439 −57439 1 NA 0.05 NA 145 TROP1 113287067 113343506 NA 0 NA NA −12420243 −12420243 1 NA 0.17 NA 146 IOCE 2665158 3520860 13 0 NA 2861062 NA 2861062 1 NA NA 0.03 147 SMARCB1 22452

50 22536703 280 0 NA 23030

90 NA 23030490 1 NA 0.02 NA 148 MTDH 88725583 98807711 7 0 NA 465352 −1031370 465352 1 NA 0.06 NA 149 NECAB2 82559738 82

78 1 0 NA 50

4 −5

52 50994 1 NA 0.07 NA 150 DEFB 88542884 88561968 0 1 63 4521 −12878 4521 1 NA 0.05 NA 151 RNF40 30831100 30595129 NA 0 NA NA −392518 −392518 1 NA NA 0.09 152 TICAM2 14942247 114988810 NA 0 NA NA −38727487 −26727467 1 NA NA 0.03 153

1 73043357 73198518 3 0 NA 265457 −1408582 265457 1 0.10 NA NA 154 MECOM 170283951 17

347354 29 0 NA 17000633 −8018470 −8012470 1 NA 0.07 NA 155 TCEB1 75021184 75048959 2 0 NA 282534 −199555 −199555 1 0.02 NA NA 156 CTNNA2 79232191 80729415 NA 0 NA NA −

819013 −28819013 1 NA NA 0.03 157 NIPAL2 99273563 99375787 1 0 NA 180240 −465852 160249 1 0.05 NA NA 158 COCA2 25372428 25421353 0 1 99 3366819 −591 −591 1 0.07 NA NA 159 WWP2 68353710 38533145 5 0 NA 405177 −57656 −57656 1 0.02 NA NA 160 DDX19A 58833322 88954280 0 1 50 6050 −408177 6058 1 0.17 NA NA 161 STX3 99807074 99907074 1 0 NA 187598 −180240 160840 1 0.02 NA NA 162 DNAH2 7577783 7577783 NA NA NA NA NA NA 1 0.02 NA NA 163 NFAT5 68296054 68296054 2 0 NA 57656 −7538258 57656 1 0.17 NA NA 164 CNGB1 66562513 99552519 3 0 NA 142487 NA 142487 1 0.02 NA NA 165 UBE2CBP 83832259 83932289 3 0 NA 144558 −7688490 144553 1 0.38 NA NA 166 C8orf10 11025155 11025155 0 1 17 154255 −697587 164255 1 0.14 NA NA 167 KIAA0196 128173191 128173121 3 0 NA 2323848 −1286883 −1286983 1 0.29 NA NA 168 CLCNK5 16258380 16256330 19 0 NA 1489527 NA 1482527 1 NA NA 0.07 169 C16orf80 56720297 56720297 10 0 NA 3624063 −142487 −142497 1 0.14 NA NA 170 ZPHX3 71

9775 71439775 2 0 NA 1453585 −2342793 14

582 1 0.14 NA NA 171 PPM1L 181956791 162871511 13 0 NA 8012470 −4212170 −4217170 1 NA 0.07 NA 172 NKRAS2 374

584 37431180 1 0 NA 75799 NA 25788 1 NA NA 0.06 173 RSPC2 108980721 106155052 9 1 42 4139255 −401262 −401282 1 0.02 NA NA 174 XPO7 21833126 21920041 3 0 NA 82617 −1577372 82619 1 0.17 NA NA 175 ME1 83976827 84197488 41 0 NA 7084576 −144558 −144558 1 0.25 NA NA 176 NLGN4Y 15144026 15466924 NA NA NA NA NA NA 1 NA NA 0.21 177 LZI31 20147956 20205754 2 0 NA 1627372 −850352 −260362 1 0.07 NA NA 178 FBXL18 5481955 5625646 NA 0 NA NA −2661062 −2861062 1 NA NA 0.04 179 TBC1010B 30275925 302

587 14 0 NA 39513 NA 392513 1 NA NA 0.03 180 WDR59 73464975 73576518 5 0 NA 243911 −266457 243811 1 0.10 NA NA 181 BLK 11338930 11459516 1 0 NA 139646 −1658681 139616 1 0.10 NA NA 182 MEPCE 99808190 99989678 2 0 NA 33404 −29540 −29450 1 NA NA 0.11 183 DLGAP2 1435920 1544048 1 0 NA 115501 NA 115501 1 NA 5.14 NA 184 ZFAT 1355

5 138794483 8 0 NA 9943223 −1218484 −1249484 1 0.17 NA NA 185 PASN 77629504 77849035 NA 1 88 NA −252 −282 1 NA NA 0.47 186 GIGYF3 100116066 100121306 1 0 NA 31653 −23059 −83059 1 NA NA 0.33 187 ANXA13 13476226 124318823 11 0 NA 1286883 −706280 −708280 1 0.10 NA NA 188 CDYL2 79196176 78995680 9 0 NA 248329 −1391644 248823 1 0.25 NA NA 189 TOX 58880531 80194321 10 0 NA 5476925 NA 5475925 1 1.23 NA NA 190 NKX2-6 23415959 23620056 6 0 NA 1478148 −129901 −129901 1 0.21 NA NA 191 RALYL 85504112 85969978 12 0 NA 1691298 −2842997 1591298 1 0.38 NA NA 192 TBG1022A 455371

45841388 NA 0 NA NA −

080490 −2

1 NA 1.40 NA 193 TFE3 48772613 48787722 NA 0 NA NA −35134932 −35134932 1 NA 0.10 NA 194 KCNAB1 157381095 157735521 22 0 NA 4817170 −12271116 4217170 1 NA 2.74 NA 195 SULP1 70841427 70738701 0 1 33 11428 −647617 11428 0 1.89 0.88 NA 196 RAB5C 37530524 37580548 0 1 64 1881 −1627 −1627 0 NA NA 0.76 197 DHX58 37508979 37518277 0 1 64 380 −75799 380 0 NA NA 4.22 198 ASAP1 131133

131433399 0 1 48 378337 −2104073 378332 0 NA 0.30 NA 199 CASA 86479126 35527518 0 1 58 14926 −18511 14926 0 0.29 0.91 NA 200 C6orf19 165513148 156643101 0 1 8 17665 −18812721 17665 0 NA NA 0.37 201 NCOA2 71178380 71478574 1 1

233471 −32264 −32264 0 0.57 0.21 NA 202 PLD1L2 79691985 79811477 0 1 53 12320 −4504 −4504 0 1.83 0.07 NA 203 BANF 86542539 86668425 0 1 58 378801 −14928 −14926 0 0.29 0.63 NA 204 KIAA1967 22510202 22533920 0 1 28 −14 −597 −14 0 0.38 0.52 NA 205 CCPG2 129933404 129935887 106 1 13 13747479 −41 −41 0 NA NA 0.53 206 ZNF708 108918444 102287136 0 1 40 282026 −243698 −243689 0 NA 0.38 NA 207 GAN 79908078 79871441 0 1 53 398967 −20828 −23825 0 0.33 0.21 NA 208 FLCG2 803713408 80549399 0 1 53 76955 −398957 76955 0 0.42 0.33 NA 209 C18orf57 13864168 13477909 0 1 68 108 −60124 108 0 NA NA 0.37 210 PSGFRL 17478443 12545655 0 1 21 −71 −6086 −71 0 1.56 NA NA 211 ESD 43248893 46263068 0 1 48 56146 −20607 −20807 0 NA NA 0.28 212 CPA5 123771892 129795307 0 1 13 11861 −20843 11661 0 NA NA 0.36 213 BIN3 22533806 22582553 0 1 26 18566 14 14 0 0.00 0.38 NA 214 ZFHX4 77756073 77949076 1 1 25 1648815 −1114478 −1114478 0 1.23 NA NA 215 DPA8 88496963 66821134 0 1 33 205773 −2623061 205773 0 0.91 NA NA 216 EYA1 78272822 72437021 0 1 34 479311 −463009 −483009 0 0.68 NA NA 217 CHRNA2 27373196 27392730 0 1 30 11832 −325 −378 0 0.74 NA NA 218 TNKS 9480858 9677286 0 1 16 271923 −522716 271823 0 1.04 NA NA 219 HNF43 76482732 76641600 0 1 35 1114478 −373386 −373386 0 1.10 NA NA 220 LRCH1 46825304 48222386 3 1 48 20867 −2766280 20607 0 NA NA 0.20 221 ACRA1A 25671584 28775836 0 1 30 320899 −89977 −39977 0 0.98 NA NA 222 EPHX2 27404582 27458433 9 1 30 185353 −11832 −11832 0 0.53 NA NA 223 SORB53 22468198 224

52 0 1 26 3247 −10616 3247 0 NA 0.47 NA 224 GRIA2 159381188 156506677 0 1 3 4017824 −48687 −48837 0 NA NA 0.17 225 POLIM2 22492199 22511488 0 1 26 1584 −3247 1584 0 NA 0.42 NA 226 MTMFP 17199923 17315207 0 1 21 89768 −1538857 33768 0 0.85 NA NA 227 FBXO94 100021892 100036674 0 1 12 1144 −180 −180 0 NA NA 0.24 228 CRISPLD1 78059531 75108048 0 1 35 373805 −129718 −129712 0 1.68 NA NA 229 CPYS 10480829 406648453 0 1 41 22190 −127566 22190 0 0.57 NA NA 230 DTNA 80377279 35725806 62 1 57 17395350 −269766 −388756 0 NA NA 0.15 231 KLHDC4 85298820 88357058 0 1 68 64075 −9857 9657 0 NA 0.25 NA 232 CYRA 87237199 87244258 0 1 58 891 −2814 891 0 NA 0.42 NA 233 JPH3 86194000 86239063 0 1 63 9857 −1098481 9857 0 0.21 0.21 NA 234 TMEM120A 75454239 75461913 0 1 10 1679 −248023 1879 0 NA NA 0.00 235 MTUS1 17545584 17703866 1 1 21 121980 71 71 0 0.80 NA NA 236 C8orf34 69405511 69393810 0 1 33 647617 −99080 −99030 0 2.37 NA NA 237 GRHL2 102574162 102750995 0 1 40 16952 −287025 16952 0 NA 0.21 NA 238 CPA2 129893839 129716370 0 1 13 3360 −29534682 3360 0 NA NA 0.11 239 NAT2 18293035 18303003 0 1 23 126090 −306243 126090 0 0.63 NA NA 240 DPYSL2 26491327 26571607 0 1 30 39977 −833035 89977 0 0.63 NA NA 241 ZDHHG7 83565573 83602642 0 1 56 16289 −84959 16269 0 NA 0.25 NA 242 ELP3 27993759 29104584 8 1 31 699245 −2452 −2452 0 0.68 NA NA 243 FRICETB2 22913059 22933655 2 1 26 115396 −306299 115396 0 NA 0.00 NA 244 NBL2 11604627 11682263 1 1 18 55179 −9709 −9709 0 0.33 NA NA 245 HR 22071877 220455326 0 1 24 6152 −4474 −4474 0 NA 0.33 NA 246 EPR3A 132985817 133005071 0 1 45 10508 −861653 10598 0 0.52 NA NA 247 STMN4 27149738 27171543 0 1 30 26478 −370899 25478 0 0.63 NA NA 248 PROM14 71126574 71146116 0 1 32 32264 −216812 32264 0 1.49 NA NA 249 MARVELD2 63746699 55773646 32 1 4 19278276 −315 −315 0 NA 0.47 NA 250 SLCSGA14 22280737 22847462 0 1 26 7079 −116113 7079 0 0.02 0.14 NA 251 ACTL6B 100078878 100092007 1 1 12 23059 −1589 −1589 0 NA NA 0.01 252 TUSC3 15442101 15666366 5 1 30 1533557 −301882 −301832 0 0.52 NA NA 253 COXANE 84569757 84390601 0 1 57 96 −27547 96 0 NA 0.25 NA 254 XKR9 717858481 71805213 0 1 34 463009 −11902 −11902 0 0.33 NA NA 255 C16orf46 79644605 79668373 0 1 53 5057 −248923 5057 0 NA 0.14 NA 256 TAF9 55895327 68701595 0 1 4 −716 −31935 −716 0 NA 0.29 NA 257 KCNG3 123210433 132581961 1 1 45 217622 −43054 −43354 0 2.37 NA NA 258 UTRN 144654566 145315859 0 1 7 772982 −20654529 772282 0 NA NA 0.18 259 RAD17 68700880 88748004 0 1 4 918 718 315 0 NA 0.09 NA 260 ZFFM1 57047226 87123398 0 1 58 18723 −378801 18723 0 NA 0.25 NA 261 PTCSS1 97343340 97415950 0 1 99 159108 −2053354 159108 0 0.25 NA NA 262 IRP8 84490275 8453710 0 1 57 587924 −92185 −92188 0 NA 0.25 NA 263 YWHAZ 101999880 108034745 0 1 40 243899 −312480 243899 0 NA 0.14 NA 264 MRP538 88549929 68577710 0 1 4 −11239 −7390 −7392 0 NA 0.29 NA 265 LACTB2 71712045 71743948 0 1 34 11802 −233471 11802 0 0.28 NA NA 266 SNA13 87271591 87280388 0 1 58 10028 −14572 10028 0 NA 0.21 NA 267 TMEM71 130779653 133842010 0 1 46 14776 −217672 18776 0 0.42 NA NA 268 PREX2 89028807 69306151 0 1 33 99050 −205773 89060 0 3.36 NA NA 269 CPA1 129807458 129815185 0 1 13 8445 −11661 8446 0 NA NA 0.09 270 PGF20L1 189856786 190930254 0 1 46 18159 −14778 −14776 0 0.33 NA NA 271 KIAA0513 83818911 83685327 2 1 58 517197 −18259 −15259 0 NA 0.10 NA 272 R15 75899327 75925819 0 1 35 129712 −457439 129712 0 0.47 NA NA 273 PCM1 17824646 17935562 0 1 22 22552 −131980 32552 0 0.00 NA NA 274 SH204A 18215433 19297594 5 1 23 850392 −303307 −300037 0 0.42 NA NA 275 C16orf74 84296624 84342190 0 1 57 27547 −18535 −18535 0 NA 0.17 NA 276 TPB3 190831910 191107935 0 1 2 49878 −2259183 49278 0 NA 0.47 NA 277 DACH1 70910099 71339931 28 1 49 19509688 −1329507 −1329507 0 NA NA 0.04 278 TNFR8F10A 93103815 29138584 0 1 27 18511 −27431 18511 0 NA 0.14 NA 279 MDH2 75516329 75533864 2 1 10 260189 −72 −72 0 NA NA 0.06 280 PAG1 82042505 82185858 3 1 37 545893 −93034 −93034 0 NA 0.07 NA 281 SLC25A37 23442308 23486008 1 1 28 129901 −71227 −71227 0 0.29 NA NA 282 BCAR1 73320429 73856452 0 1 51 25657 −243911 25657 0 0.25 NA NA 283 COX411 86290697 84398109 0 1 57 92166 −96 −98 0 NA 0.29 NA 284 EIF4H 73226625 73249300 0 1 9 12304 −404099 12304 0 NA NA 0.07 285 ZC3H13 87164343 87225758 0 1 58 6746 −294 −294 0 NA 0.10 NA 286 STMN2 80685916 80740668 0 1 36 97999 −1007676 97933 0 0.38 NA NA 287 AFG3L1 88565489 88594695 1 1 63 21813 −4521 −4521 0 NA 0.17 NA 288 HS017B2

64 80689638 1 1 53 750123 −76965 −76965 0 0.29 NA NA 289 MYO 87245849 87257019 0 1 58 14572 −891 −891 0 NA 0.17 NA 290 DLC1 13985743 13418766 1 1 18 574978 −53580 −53580 0 2.71 NA NA 291 EPHA7 94007864 94185993 9 1 5 6242082 −2654208 −2654236 0 NA NA 0.01 292 TRIM35 27198321 27294751 0 1 30 165 −26479 165 0 0.29 NA NA 293 LRRC56 82736365 82769024 3 1 54 116798 −101 −101 0 0.21 NA NA 294 CNG83 87655277 87885017 0 1 38 122823 −1691293 122823 0 0.02 NA NA 295 ASCC3 101062791 101435961 79 1 6 16667349 −43297 −43297 0 NA NA 0.02 296 FIFC2 73283770 73806674 0 1 9 35065 −1671 −1671 0 NA NA 0.03 297 CLEC3A 76513944 76623495 0 1 52 67557 −280292 57557 0 0.17 NA NA 298 IL17C 87232502 87234385 0 1 58 2814 −6746 2814 0 NA 0.02 NA 299 BMP1 22078545 22125782 0 1 25

330 −8355 7380 0 NA 0.14 NA 300 CFA4 129720230 129751249 0 1 13 20843 −3360 −3360 0 NA NA 0.08 301 CC90 138105587 133167084 0 1 45 43354 −10596 −10596 0 0.05 NA NA 302 HEPH 65298388 85403358 0 1 59 328245 NA 325243 0 0.02 NA NA 303 LRP12 105570543 105570344 0 1 41 729979 −22190 −22190 0 NA 0.07 NA 304 AGFG2 99974770 100003778 0 1 12 5798 −44412 5798 0 NA NA 0.18 305 TRPA1 73095640 23180373 0 1 34 482151 −176785 −176755 0 0.17 NA NA 306 GRNS2 84268788 84280089 0 1 57 18535 −1471 −1471 0 NA 0.10 NA 307 CENPH 68521131 68541839 0 1 4 7390 NA 7390 0 NA 0.05 NA 308 KLHL38 83239632 89253416 0 1 56 37634 −143833 37834 0 NA 0.02 NA 309 ARHGBPOIU 17738917 17895356 0 1 1 57439 −1482527 57439 0 NA 0.10 NA 310 TRAPPC2L 87451007 57455020 0 1 60 13748 −122 −122 0 NA 0.05 NA 311 TCF25 88457520 88502287 0 1 62 7881 −2292 −2292 0 NA 0.10 NA 312 TNFRSF180 23649051 22077485 0 1 27 27431 −115396 27431 0 5.05 NA NA 313 MYOM3 1980598 2080779 0 1 14 699503 −88059 −98359 0 0.10 NA NA 314 GCSH 7673430 79637481 0 1 53 4504 −5057 4504 0 NA 0.05 NA 315 KIAA1809 88068808 83095294 1 1 55 143358 −15818 −15815 0 NA 0.05 NA 316 FANCA 88331480 88410566 0 1 62 11842 −245990 11842 0 NA 0.08 NA 317 ER

8897858 8938138 1 1 15 522716 −109315 −109315 0 0.65 NA NA 318 HSOL1 88713389 82736265 0 1 54 101 −5371 101 0 NA 8.07 NA 319 KIAA0182 84202524 84287811 0 1 67 1471 −

17197 1471 0 NA 0.07 NA 320 CBFA2T3 87468758 87570902 2 1 80 1947

−

45 −13748 0 NA 0.05 NA 321 EGR3 22601119 22605760 0 1 26 306299 −18566 −18568 0 NA 0.07 NA 322 POGLCE 103037818 100043732 0 1 12 3929 −1144 −1144 0 NA NA 0.02 323 C18orf85 87147613 87164049 0 1 58 294 −18729 294 0 NA 0.10 NA 324 HMBOX1 288

289

05 0 1 32 14009 −599246 34009 0 0.02 NA NA 325 MTMR9 1178410 11283052 8 1 17 165

−164255 −154255 0 0.05 NA NA 326 MSC 72916332 72919285 0 1 34 176755 −479311 176755 0 0.07 NA NA 327 ST

GAL2 89970835 69030492 35 1 50 2343793 −

−6053 0 0.21 NA NA 328 FOXF1 85101634 85105670 0 1 57 15714 −

87924 15714 0 NA 0.14 NA 329 C8orf58 32519067 22817605 0 1 26 897 −1584 897 0 NA 0.47 NA 330 KCTD9 25841283 25971857 0 1 20 591 −14747 591 0 0.07 NA NA 331 ANGFT1 108890899 108579459 0 1 4

401362 −1441960 401252 0 0.21 NA NA 332 GDAP1 75425173 75441885 0 1 35 457439 −29055 −29056 0 0.07 NA NA 333 RNF168 87290411 87300012 1 1 58 2804 −10025 2804 0 NA 0.14 NA 334 KLHL1 69178727 69680692 0 1 49 1829507 −2470149 1329507 0 NA NA 0.04 335 LOXL2 23210097 23317667 0 1 28 −18281 −34647 −18281 0 NA 0.08 NA 336 WISP1 134278494 134310751 2 1 40 1245464 −88015 −88013 0 0.14 NA NA 337 C8orf80 27905807 27597307 0 1 31 2452 −29480 2452 0 0.80 NA NA 338 LAT2 732

882 732

099 0 1 9 1671 −12304 1671 0 NA NA 0.06 339 USP10 83291050 83371028 0 1 58 40087 −37534 −37814 0 0.17 NA NA 340 CDH15 87765664 87789400 0 1 61 72136 −184762 72138 0 NA 0.05 NA 341 WFDC1 828

822 82920886 0 1 55 38746 −116798 31746 0 0.17 NA NA 342 C7orf51 99919488 99930658 0 1 12 44412 −4648 −4648 0 NA NA 0.13 343 ESP2 25758042 25958292 2 1 29 533

5 −336689 −390089 0 1.76 NA NA 344 GCDC125 69612278 88654198 0 1 4 31935 −3274 −3274 0 NA 0.07 NA 345 LG13 22060290 22070290 1 1 24 8856 −4897 −4897 0 NA 0.07 NA 346 NUDT18 22020328 22023403 0 1 24 4474 −2493 −2493 0 NA 0.17 NA 347 PHYH1P 22153158 22145798 0 1 25 12758 −7380 −7380 0 NA 0.14 NA 348 PILRA 99859004 99835850 1 1 11 29540 −8616 −8816 0 NA NA 0.0

349 KAT2A 375

57 37525872 0 1 64 14

−

0 −380 0 NA NA 0.57 350 CSMD3 113304337 114518418 0 1 43 1871482 −4138265 1

1482 0 1.63 1.16 NA 351 REEP4 22051478 22055393 0 1 24 4897 −6152 4897 0 NA 0.25 NA 352 TUBB3 88613168 88530006 1 1 62 12678 −7881 −3881 0 NA 0.29 NA 353 CDT1 87987682 874

65 1 1 69 4473 −67370 4478 0 NA 0.07 NA 354 EDA2R 68732204 65778608 0 1 69 904961 −325248 −328248 0 0.07 NA NA 355 DUS1L 77609043 77629242 0 1 68 252 −40474 262 0 NA NA 0.16 356 LRCH48 109009520 100021712 0 1 12 180 −5792 180 0 NA NA 0.12 357 TMEM75 129029048 129029462 2 1 44 2104073 −206198 −206183 0 0.74 NA NA 358 NUDT7 76313912 76333652 0 1 52 280292 −287400 280292 0 0.14 NA NA 359 TSGA14 129823611 129863139 0 1 13 45149 −8446 −8446 0 NA NA 4.49 360 CDC42BPG 84343240 6438

617 2 1 47 80139 −12803 −12

0 NA NA 0.18 361 TSC22D4 99802083 99914838 0 1 12 4648 −33404 4648 0 NA NA 0.11 362 NOTUM 77503589 77512083 0 1 65 18362 −3990

67 16362 0 NA NA 0.32 363 HSPB8 37528361 37528687 0 1 64 1627 −1489 −1489 0 HA NA 0.44 364 TFR2 100055875 100077109 0 1 12 1569 −5043 156

0 HA NA 0.29 365 SLA 134118155 134184479 0 1 46 88015 −98170 82015 0 0.14 NA NA 366 WWOX 75591052 77803532 2 1 52 1391544 −57537 −67567 0 4.45 NA NA 367 POU5F1B 128497039 128498621 0 1 44 318241 −23

548 318241 0 0.42 NA NA 368 OPHN1 67179440 67570372 NA 1 69 NA −318598 −318598 0 3.24 NA NA

indicates data missing or illegible when filed 

1. A method of diagnosing and treating a human subject who has or had breast or lung cancer, the method comprising (a) obtaining a tissue or DNA sample from the subject, (b) determining in the sample the number of copies per cell of at least 12 genes and/or genomic regions of a metastatic gene signature set, wherein the metastatic gene signature set consists of the PPP3CC genomic region, the SLCO5A1 genomic region, the SLC7A5 genomic region, the SLC7A2 genomic region, the CRISPLD2 genomic region, the CDH13 gene, the CDH8 gene, the CDH2 gene, the ASAH1 genomic region, the KCNB2 genomic region, the KCNH4 genomic region, the CTD8 gene, the JPH1 genomic region, the MEST genomic region, the NCALD genomic region, the COL19A1 gene, the MAP3K7 genomic region, the YWHAG gene, the NOL4 genomic region, and the ENOX1 gene, wherein said detecting comprises performing nucleic acid hybridization, and wherein the PPP3CC genomic region consists of the genes PPP3CC, KIAA1967, BIN3, SORBS3, PDLIM2, RHOBTB2, SLC39A14, EGR3, and C8orf58, the SLC05A1 genomic region consists of the genes SLC05A1, SULF1, NCOA2, CPA6, C8orf34, PRDM14, and PREX2, the SLC7A5 genomic region consists of the genes SLC7A5, CA5A, BANP, KLHDC4, CYBA, JPH3, ZFPM1, SNAI3, ZC3H18, MVD, IL17C, C16orf85, and RNF166, the SLC7A2 genomic region consists of the genes SLC7A2, MTMR7 and MTUS1, the CRISPLD2 genomic region consists of the genes CRISPLD2, ZDHHC7, KIAA0513, KLHL36, and USP10, the ASAH1 genomic region consists of the genes ASAH1 and PCM1, the KCNB2 genomic region consists of the genes KCNB2, EYA1, XKR9, and TRPA1, the KCNH4 genomic region consists of the genes KCNH4, RAB5C, DHX58, KAT2A, and HSPB9, the JPH1 genomic region consists of the genes JPH1, HNF4G, CRISPLD1, P15, and GDAP1, the MEST genomic region consists of the genes MEST, COPG2, CPA5, CPA2, CPA1, CPA4, and TSGA14, the NCALD genomic region consists of the genes NCALD, ZNF706, GRHL2, and YWHAZ, the MAP3K7 genomic region consists of the genes MAP3K7 and EPHA7, and the NOL4 genomic region consists of the genes NOL4 and DTNA, (c) determining an aggregate score at least 12 members as compared to the number of copies per cell in non-cancer cells, (d) based on the determination in step (c), diagnosing that the subject has risk of metastasis, and (e) treating the subject with at least one therapy selected from the group consisting of surgery, radiation therapy, chemotherapy or biologically targeted therapy.
 2. The method of claim 1, wherein the at least 12 genes and/or genomic regions include the PPP3CC genomic region, the SLCO5A1 genomic region, the SLC7A5 genomic region, the SLC7A2 genomic region, the CRISPLD2 genomic region, the CDH13 gene, the CDH8 gene, the CDH2 gene, the ASAH1 genomic region, the KCNB2 genomic region, the KCNH4 genomic region, and the CTD8 gene.
 3. The method of claim 1, wherein the at least 12 genes and/or genomic regions include all of the genes and genomic regions in said metastatic gene signature set. 4.-23. (canceled)
 24. The method of claim 3, further comprising determining the number of copies per cell of at least one additional gene or genomic region selected from the group consisting of PPP3CC, SLCO5A1, SLC7A5, SLC7A2, CRISPLD2, CDH13, CDH8, CDH2, ASAH1, KCNB2, KCNH4, KCTD8, JPH1, MEST, NCALD, COL19A1, MAP3K7, YWAHG, NOL4, ENOX1, CSMD1, SGCZ, PDE10A, PCDH9, HTR2A, HIP1, CD226, DCC, CC2D1A, PTK2B, BCMO1, MACRDO1, GRID2, DIAPH3, PILRB, MEIS2, MSRA, DPYD, ANKRD11, NRXN1, ADCY8, TRDN, STAU2, SF1, CLIP2, CLDN3, ZSWIM4, GLRB, DCHS2, TRPS1, MDGA2, CNBD1, STAG3, GATA4, VPS13B, DOCK5, ZHX2, ARHGEF5, SDC2, MYLK, LPHN3, MOSPD3, GYS2, GAS8, RAB9A, POLR3D, PSD3, ZFPM2, ATP6V1C1, MEF2C, PKIA, ADAMTS18, STYXL1, EPM2A, LEPRELI, GABRA2, RCOR2, MFHAS1, SCARA5, CCDC25, FAM38A, CTSB, PTK2, SPIRE2, C13orf23, BODIL, FAM160B2, NUS1, MTHFSD, UBR5, GALNS, FSTL5, SIM1, TG, BFSP2, MMP16, RIMS2, PDS5B, CDK7, CNTNAP4, CFDP1, FBXL4, RFX1, NALCN, STX1A, CYP7B1, ARHGEFO, ENTPD4, ZNF704, C8orf79, SLC9A9, CHMP7, GPC5, MYC, STIP1, ZBTB20, MEN1, SLC26A7, ALCAM, KIF13B, MBTPS1, PPP2R5B, VPS13C, ASPRSCR1, EPO, HEYl, KALRN, RGS22, WDR7, COL11A1, GHDC, ATP2C2, CDH17, DGKG, GRK5, GRM1, IMPA1, RPL7, COL21A1, COL12A1, MLYCD, AR, PLCB1, ACTL8, TFDP1, IQCE, SMARCB1, MTDH, NECAB2, DEF8, RNF40, TICAM2, GLG1, MECOM, TCEB1, CTNNA2, NIPAL2, CDCA2, WWP2, DDX19A, STK3, DNAH2, NFAT5, CNGB1, UBE2CBP, C8orf16, KIAA0196, CLCNKB, C16orf80, ZFHX3, PPM1L, NKIRAS2, RSPO2, XPO7, MEl, NLGN4Y, LZTS1, FBXL18, TBCD10B, WDR59, BLK, MEPCE, DLGAP2, ZFAT, FASN, GIGYFI, ANXA13, CDYL2, TOX, NKX2-6, RALYL, TBC1D22A, TFE3, KCNAB1, SULF1, RAB5C, DHX58, ASAP1, CA5A, C6orf118, NCOA2, PKD1L2, BANP, KIAA1967, COPG2, ZNF706, GAN, PLCG2, C19orf57, PDGFRL, ESD, CPA5, BIN3, ZFHX4, CPA6, EYA1, CHRNA2, TNKS, HNF4G, LRCH1, ADRAIA, EPHX2, SORBS3, GRIA2, PDLIM2, MTMR7, FBXO24, CRISPLD1, DPYS, DTNA, KLHDC4, CYBA, JPH3, TMEM120A, MTUS1, C8orf34, GRHL2, CPA2, NAT2, DPYSL2, ZDHHC7, ELP3, RHOBTB2, NEIL2, HR, EFR3A, STMN4, PRDM14, MARVELD2, SLC39A14, ACTL6B, TUSC3, COX4NB, XKR9, C16orf46, TAF9, KCNQ3, UTRN, RAD17, ZFPM1, PTDSS1, IRF8, YWHAZ, MRPS36, LACTB2, SNAI3, TMEM71, PREX2, CPA1, PHF20L1, KIAA0513, PI15, PCM1, SH2D4A, C16orf74, TP63, DACH1, TNFRSF10A, MDH2, PAG1, SLC25A37, BCAR1, COX4I1, EIF4H, ZC3H18, STMN2, AFG3L1, HSD17B2, MVD, DLC1, EPHA7, TRIM35, LRRC50, CNGB3, ASCC3, RFC2, CLEC3A, IL17C, BMP1, CPA4, OC90, HEPH, LRP12, AGFG2, TRPA1, GINS2, CENPH, KLHL36, ARHGEFOL, TRAPPC2L, TCF25, TNFRSF10D, MYOM2, GCSH, KIAA1609, FANCA, ERIl, HSDL1, KIAA0182, CBFA2T3, EGR3, PCOLCE, C16orf85, HMBOX1, MTMR9, MSC, ST3GAL2, FOXF1, C8orf58, KCTD9, ANGPT1, GDAP1, RNF166, KLHL1, LOXL2, WISP1, C8orf80, LAT2, USP10, CDH15, WFDC1, C7orf51, EBF2, CCDC125, LGI3, NUDT18, PHYHIP, PILRA, KAT2A, CSMD3, REEP4, TUBB3, CDT1, EDA2R, DUS1L, LRCH4, TMEM75, NUDT7, TSGA14, CDC42BPG, TSC22D4, NOTUM, HSPB9, TFR2, SLA, WWOX, POU5F1B, and OPHN1.
 25. The method of claim 24, wherein said at least one additional gene or genomic region comprises 20 genes and/or genomic regions selected from the group consisting of PPP3CC, SLCO5A1, SLC7A5, SLC7A2, CRISPLD2, CDH13, CDH8, CDH2, ASAH1, KCNB2, KCNH4, KCTD8, JPH1, MEST, NCALD, COL19A1, MAP3K7, YWAHG, NOL4, ENOX1, CSMD1, SGCZ, PDE10A, PCDH9, HTR2A, HIP1, CD226, DCC, CC2D1A, PTK2B, BCMO1, MACRDO1, GRID2, DIAPH3, PILRB, MEIS2, MSRA, DPYD, ANKRD11, NRXN1, ADCY8, TRDN, STAU2, SF1, CLIP2, CLDN3, ZSWIM4, GLRB, DCHS2, TRPS1, MDGA2, CNBD1, STAG3, GATA4, VPS13B, DOCK5, ZHX2, ARHGEF5, SDC2, MYLK, LPHN3, MOSPD3, GYS2, GAS8, RAB9A, POLR3D, PSD3, ZFPM2, ATP6V1C1, MEF2C, PKIA, ADAMTS18, STYXL1, EPM2A, LEPRELI, GABRA2, RCOR2, MFHAS1, SCARA5, CCDC25, FAM38A, CTSB, PTK2, SPIRE2, C13orf23, BODIL, FAM160B2, NUS1, MTHFSD, UBR5, GALNS, FSTL5, SIM1, TG, BFSP2, MMP16, RIMS2, PDS5B, CDK7, CNTNAP4, CFDP1, FBXL4, RFX1, NALCN, STX1A, CYP7B1, ARHGEFO, ENTPD4, ZNF704, C8orf79, SLC9A9, CHMP7, GPC5, MYC, STIP1, ZBTB20, MEN1, SLC26A7, ALCAM, KIF13B, MBTPS1, PPP2R5B, VPS13C, ASPRSCR1, EPO, HEYl, KALRN, RGS22, WDR7, COL11A1, GHDC, ATP2C2, CDH17, DGKG, GRK5, GRM1, IMPA1, RPL7, COL21A1, COL12A1, MLYCD, AR, PLCB1, ACTL8, TFDP1, IQCE, SMARCB1, MTDH, NECAB2, DEF8, RNF40, TICAM2, GLG1, MECOM, TCEB1, CTNNA2, NIPAL2, CDCA2, WWP2, DDX19A, STK3, DNAH2, NFAT5, CNGB1, UBE2CBP, C8orf16, KIAA0196, CLCNKB, C16orf80, ZFHX3, PPMIL, NKIRAS2, RSPO2, XPO7, MEl, NLGN4Y, LZTS1, FBXL18, TBCID10B, WDR59, BLK, MEPCE, DLGAP2, ZFAT, FASN, GIGYFI, ANXA13, CDYL2, TOX, NKX2-6, RALYL, TBC1D22A, TFE3, KCNAB1, SULF1, RAB5C, DHX58, ASAP1, CA5A, C6orf118, NCOA2, PKD1L2, BANP, KIAA1967, COPG2, ZNF706, GAN, PLCG2, C19orf57, PDGFRL, ESD, CPA5, BIN3, ZFHX4, CPA6, EYA1, CHRNA2, TNKS, HNF4G, LRCH1, ADRAIA, EPHX2, SORBS3, GRIA2, PDLIM2, MTMR7, FBXO24, CRISPLD1, DPYS, DTNA, KLHDC4, CYBA, JPH3, TMEM120A, MTUS1, C8orf34, GRHL2, CPA2, NAT2, DPYSL2, ZDHHC7, ELP3, RHOBTB2, NEIL2, HR, EFR3A, STMN4, PRDM14, MARVELD2, SLC39A14, ACTL6B, TUSC3, COX4NB, XKR9, C16orf46, TAF9, KCNQ3, UTRN, RAD17, ZFPM1, PTDSS1, IRF8, YWHAZ, MRPS36, LACTB2, SNAI3, TMEM71, PREX2, CPA1, PHF20L1, KIAA0513, PI15, PCM1, SH2D4A, C16orf74, TP63, DACH1, TNFRSFOA, MDH2, PAG1, SLC25A37, BCAR1, COX4I1, EIF4H, ZC3H18, STMN2, AFG3L1, HSD17B2, MVD, DLC1, EPHA7, TRIM35, LRRC50, CNGB3, ASCC3, RFC2, CLEC3A, IL17C, BMP1, CPA4, OC90, HEPH, LRP12, AGFG2, TRPA1, GINS2, CENPH, KLHL36, ARHGEFOL, TRAPPC2L, TCF25, TNFRSF10D, MYOM2, GCSH, KIAA1609, FANCA, ERIl, HSDL1, KIAA0182, CBFA2T3, EGR3, PCOLCE, C16orf85, HMBOX1, MTMR9, MSC, ST3GAL2, FOXF1, C8orf58, KCTD9, ANGPT1, GDAP1, RNF166, KLHL1, LOXL2, WISP1, C8orf80, LAT2, USP10, CDH15, WFDC1, C7orf51, EBF2, CCDC125, LGI3, NUDT18, PHYHIP, PILRA, KAT2A, CSMD3, REEP4, TUBB3, CDT1, EDA2R, DUS1L, LRCH4, TMEM75, NUDT7, TSGA14, CDC42BPG, TSC22D4, NOTUM, HSPB9, TFR2, SLA, WWOX, POU5F1B, and OPHN1.
 26. The method of claim 25, wherein said 20 genes and/or genomic regions consist of CSMD1, SGCZ, PDE10A, PCDH9, HTR2A, HIP1, CD226, DCC, CC2D1A, PTK2B, BCMO1, MACRDO1, GRID2, DIAPH3, PILRB, MEIS2, MSRA, DPYD, ANKRD11, and NRXN1. 